Plasma and urine metabolic fingerprinting of type 1 diabetic children

Balderas, Claudia; Rupérez, Javier; Ibáñez, Elena; Señorans, Javier; Fernández, J; Casado, Isabel González; Gracia-Bouthelier, Ricardo; Garcı́a, Antonia; Barbas, Coral

doi:10.1002/elps.201300062

Cited by 62 publications

(60 citation statements)

References 76 publications

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“…Taking these results into account, the obtained reproducibility in the chromatographic analysis and the consulted bibliography (Balderas et al 2013;Ciborowski et al 2012;Ferrarini et al 2013), the study was carried out with a cold mixture of methanol:ethanol (1:1).…”

Section: Samples Extraction and Repeatabilitymentioning

confidence: 99%

Metabolomics in non-arteritic anterior ischemic optic neuropathy patients by liquid chromatography–quadrupole time-of-flight mass spectrometry

et al. 2014

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Non-Arteritic Anterior Ischemic Optic Neuropathy (NAION) is a rare ischemic disease that affects the optic nerve. Pathophysiology and mechanism of ischemia of NAION remain uncertain, so the aim of this work is to establish the first metabolic fingerprinting of patients with NAION to discover possible new biomarkers. Twenty-four patients, aged 39-85 years, diagnosed with NAION, after a sudden loss of vision, were recruited for the study. Plasma samples of patients and controls were fingerprinted with liquid chromatography coupled to quadrupole time-offlight by electrospray ionization, and obtained data were filtered, aligned and statistically analysed to identify new biomarkers. The identity of compounds that were found to be significant in class separation was later confirmed by obtaining the characteristic MS/MS spectra and online databases. In general, biochemical and metabolic profiles between patients and controls did not show profound differences, but NAION patients presented disturbances in the phospholipid composition which lead to reduced plasma values of LysoPCs. Altered levels of other metabolites, such as L-Palmitoylcarnitine, have been detected and could be considered as potential biomarkers.

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Section: Samples Extraction and Repeatabilitymentioning

confidence: 99%

Metabolomics in non-arteritic anterior ischemic optic neuropathy patients by liquid chromatography–quadrupole time-of-flight mass spectrometry

et al. 2014

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“…Importantly, CE also gives complementary information to HILIC [13], as well as, significantly better peak shape in many cases. It is therefore not surprising that CE-MS has already been considered for multiple metabolomics studies covering several applications, from aging [19], amino acid analysis [20,21] [46][47][48][49][50][51][52][53], CVD [54][55][56][57][58], diabetes [59][60][61][62][63][64][65], lifestyle [61][62][63][64][65][66][67][68][69][70][71], kidney disease [72,73], liver disease [74][75][76][77][78][79][80][81][82], the microbiome [83][84]…”

Section: Current Advantages and Biotechnology Applicationsmentioning

confidence: 99%

Capillary electrophoresis mass spectrometry based metabolomics

Buko¹

2017

J Appl Bioanal

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IntroductionSince its first formal definition more than a decade ago, metabolomics, or, the comprehensive analysis of all metabolites present within a biological system, has attracted growing interest in clinical research by academia, industry and government labs. This is most prevalent in biomarker and drug development applications where a considerable change has been witnessed in how new diagnoses, prognoses, and therapeutic options are being discovered and developed using omic technologies. Moreover, many chronic diseases suggest a strong metabolic involvement or even a clear metabolic cause, including cancer. Together with the other omic disciplines, including genomics and proteomics, metabolomics plays a key role in the implementation of personalized medicine; evidence-based medicine designed for individually designed healthcare strategies. In turn, biomarker discovery and the understanding of biochemical pathways typically rely on a multimodal approach. Among these modalities, there continues to be a growing interest in CE-MS based development and implementation in clinical development. Formulating the problemDepending on how you classify the metabolome, there is a complex chemical space separated by hydrophilicity, polarity and size, excluding a broad range of metabolites classified as lipids, separately referred to as lipidomics. This class of metabolites also covers a large range of physical properties for which specifically designed platforms work the best. For example, for years liquid chromatography-mass spectrometry (LC-MS) has been used to capture a host of hydrophilic and hydrophobic metabolites, while gas chromatography-mass spectrometry (GC-MS) has been used to capture small molecular weight metabolites. For this review, the metabolome refers to endogenous molecules with a molecular weight typically less than 1000 Kd. To measure, catalogue, and compare the entirety of the metabolic space, the implementation of comprehensive mass spectral databases was needed (e.g., Human Metab- Because of this diversity in physical properties and size of the metabolome in biological systems, there has been a need for the development of several analytical protocols based on different chromatographic methods to select specific subgroups of metabolites based on these different chemical properties beyond the technical capabilities of LC-MS and GC-MS. These new methods have their own advantages for selecting specific types of molecules: lipids, nucleotides, aminoacids or steroids. Nonmass spectrometric methods such as nuclear magnetic resonance (NMR) and non-chromatographic methods such as matrix-assisted laser desorption-time of flight (MALDI-TOF) imaging are successfully being used for selected metabolomic analyses. The focus of this review is recent publications that use CE-MS to extend the polar metabolome beyond what is observed by LC-MS and GC-MS. Metabolomics -current methods

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“…Some of the metabolites associated with T1D were identified, among which guanidinoacetate, creatinine, urea, phenyllactate and p-OH-phenyllactate, phenaceturate, and benzoate. To analyze more in depth the metabolic changes characterizing T1D children, Balderas et al [32] later also investigated the alterations in plasma and urine of T1D diabetic children who were under insulin treatment with good glycemic control. Plasma samples were analyzed with LC-MS, while urines with CE-MS.…”

Section: Metabolomics and Nutrition In Pediatricsmentioning

confidence: 99%

Clinical Metabolomics and Nutrition: The New Frontier in Neonatology and Pediatrics

Dessì

Marincola

Masili

et al. 2014

BioMed Research International

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In the pediatric clinic, nutritional research is focusing more and more on preventing the development of long-term diseases as well as supporting the repair processes important in the therapy of already fully developed diseases. Most children who are hospitalized or affected by chronic diseases could benefit from specific and careful attention to nutrition. Indeed, the state of nutrition modulates all body functions, including the different metabolic processes which, all together, have a profound effect on the development of the health and future of all individuals. Inappropriate food, even in the first periods of life, can accelerate the development of chronic metabolic diseases, especially in the pediatric age. To gain further insights into metabolic cycles and how they are connected with diet and health, nutrition and metabolomics interact to develop and apply modern technologies for metabolic assessment. In particular, nutritionists are evaluating the metabolomic approach to establish the single nutritional phenotypes, that is, the way in which diet interacts with individuals' metabolisms. This strategy offers the possibility of providing a complete definition of the individual's nutritional and health status, predict the risk of disease, and create metabolomic databases supporting the development of “personalized nutrition,” in which diet is attuned to the nutritional needs of individual patients.

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Plasma and urine metabolic fingerprinting of type 1 diabetic children

Cited by 62 publications

References 76 publications

Metabolomics in non-arteritic anterior ischemic optic neuropathy patients by liquid chromatography–quadrupole time-of-flight mass spectrometry

Metabolomics in non-arteritic anterior ischemic optic neuropathy patients by liquid chromatography–quadrupole time-of-flight mass spectrometry

Capillary electrophoresis mass spectrometry based metabolomics

Clinical Metabolomics and Nutrition: The New Frontier in Neonatology and Pediatrics

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