Serum Glycerophosphate Levels are Increased in Japanese Men with Type 2 Diabetes

Daimon, Makoto; Soga, Tomoyoshi; Hozawa, Atsushi; Oizumi, Toshihide; Kaino, Wataru; Takase, Kaoru; Karasawa, Shigeru; Jimbu, Yumi; Wada, Kiriko; Kameda, Wataru; Susa, Shinji; Kayama, Takamasa; Saito, Kaori; Tomita, Masaru; Kato, Takeshi

doi:10.2169/internalmedicine.51.6612

Cited by 10 publications

(14 citation statements)

References 21 publications

(21 reference statements)

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“…In metabolomics CE‐MS is especially suitable for urine fingerprinting , what can be performed with minimal sample preparation . Analysis of serum or plasma samples by CE‐MS requires more complicated sample treatment, however, this technique can also be used to measure successfully metabolic profiles of this type of samples . CE‐MS‐based metabolomics has been used to study many diseases, including cancer , neurodegenerative diseases , acute lung injury , or diabetes .…”

Section: Introductionmentioning

confidence: 99%

“…Analysis of serum or plasma samples by CE‐MS requires more complicated sample treatment, however, this technique can also be used to measure successfully metabolic profiles of this type of samples . CE‐MS‐based metabolomics has been used to study many diseases, including cancer , neurodegenerative diseases , acute lung injury , or diabetes . More details about these studies can be found in several reviews about application of CE‐MS in metabolomics research, which have been publish last years’ .…”

Section: Introductionmentioning

confidence: 99%

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CE‐MS‐based serum fingerprinting to track evolution of type 2 diabetes mellitus

et al. 2015

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Development of type 2 diabetes mellitus (T2DM) is preceded by insulin resistance (IR), which may evolve to impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT). IFG and IGT are considered as prediabetic states (PD). Prediabetes indicates the high risk for the future development of diabetes, it is estimated that up to 70% of prediabetics eventually develop T2DM. The risk of T2DM development is increased in overweight (OW) and obese (OB) people; however normal weight (NW) individuals also suffer from T2DM. The present study was designed to evaluate whether changes in polar metabolites induced by T2DM evolution are different between NW, overweight and obese individuals. CE-MS serum fingerprinting was performed on 197 serum samples obtained from OW, OB, and NW humans whom were IR, prediabetics, diabetics or with normal glucose homeostasis. Metabolic changes evoked by the progression of T2DM differ between obese, overweight, and normal weight subjects. Based on obtained results several metabolites can be proposed as a promising target to track T2DM evolution; BCAA in OW and NW humans, lysine in OB, while acetylcarnitine and methionine independently on body mass index. Validation of obtained results on larger population is required.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

CE‐MS‐based serum fingerprinting to track evolution of type 2 diabetes mellitus

et al. 2015

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“…CE‐MS‐based metabolomics studies revealed important findings in the various application areas as outlined in this review. For example, the use of this approach revealed γ‐glutamyl dipeptides as novel biomarkers for liver diseases , serum glycerol‐3‐phospate as a marker for predicting glucose intolerance , provided insight into the cytotoxic mechanism of seleno‐methionine and insight into the storage conditions of various foods .…”

Section: Discussionmentioning

confidence: 99%

“…Daimon et al used a similar CE‐MS approach for comprehensive profiling of metabolites in serum of Japanese males with diabetes . Of the 560 metabolites detected by the CE‐MS platform, the levels of 74 metabolites were quantified in all of the serum samples.…”

Section: Applicationsmentioning

confidence: 99%

CE‐MS for metabolomics: Developments and applications in the period 2010–2012

2012

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CE-MS has emerged as a powerful technique for the profiling of (highly) polar and charged metabolites in biological samples. This review provides an update of the most recent developments in CE-MS for metabolomics covering the scientific literature from July 2010 to June 2012. The present paper is an update of two previous review papers covering the years 2000-2010 (Electrophoresis 2009, 30, 276-291; Electrophoresis 2011, 32, 52-65). Emerging technological developments used in CE-MS for metabolomics are discussed, such as the use of novel interfacing techniques for coupling CE to MS. Representative examples illustrate the applicability of CE-MS in the fields of biomedical, clinical, microbial, plant, environmental and food metabolomics. Concerning targeted and non-targeted approaches, a comprehensive overview of recent CE-MS-based metabolomics studies is given in a table. Information on sample type and pretreatment, capillary coatings and MS detection mode is provided. Finally, general conclusions and perspectives are provided.

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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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Serum Glycerophosphate Levels are Increased in Japanese Men with Type 2 Diabetes

Cited by 10 publications

References 21 publications

CE‐MS‐based serum fingerprinting to track evolution of type 2 diabetes mellitus

CE‐MS‐based serum fingerprinting to track evolution of type 2 diabetes mellitus

CE‐MS for metabolomics: Developments and applications in the period 2010–2012

Capillary electrophoresis mass spectrometry based metabolomics

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