Metabolomics and Diabetes: Analytical and Computational Approaches

Sas, Kelli M.; Karnovsky, Alla; Michailidis, George; Pennathur, Subramaniam

doi:10.2337/db14-0509

Cited by 145 publications

(123 citation statements)

References 136 publications

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“…Several techniques have been developed to survey molecular alteration to clarify the pathogenesis of diseases (11). One of the powerful tools in biomarker discovery is metabolomics that can illuminate the underlying biology and discover clinical markers of diseases us-ing bioinformatics pathway analysis (12). In recent years, some metabolomics studies in biomarker discovery have been reported on various diseases by our group (13)(14)(15)(16).…”

Section: Introductionmentioning

confidence: 99%

Serum Metabolic Profiling of Advanced Cirrhosis Based on HCV

et al. 2017

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Background: Cirrhosis is recognized by a reduction in hepatocyte proliferation with an increase in fibrous tissue, which may ultimately lead to the development of cancerous nodules. Liver biopsy has remained the gold standard for confirming liver fibrosis stages, but there are not any nonreversible and specific therapeutic targets in advanced cirrhosis. In the present study, we used the NMR method to find potential therapeutic markers in serum of HCV -cirrhotic patients with advanced stage.Methods: A metabolic profiling study was conducted using 2 groups: decompensated HCV-cirrhosis patients (n = 21) and healthy controls (n = 18). 1H nuclear magnetic resonance (NMR) approach was used to obtain the serum metabolic profiles of the samples. The acquired data were processed by the multivariate principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Moreover, metabolic pathways were determined using MetaboAnalyst 3.0.Results: Specifically, 16 metabolites showed alteration between the 2 groups. Compared with healthy controls, a number of metabolites showed increased concentration in serum of decompensated HCV-cirrhosis such as succinic acid, isovaleraldehyde, citrulline, propanal and cinnamaldehyde, while several others were observed in decreased levels in the decompensated HCV-cirrhosis such as valine, glutamine, trimethylamine, lactate, proline, aspartate, lipid, VLDL, isoleucine, fucose, and glutamate. Aminoacyl-tRNA biosynthesis, alanine, aspartate, glutamate metabolism and arginine, and proline metabolism are the most significant pathways associated with advanced HCV-cirrhosis. Conclusions:Metabolomic profiling through NMR can identify the metabolic disturbances in advanced HCV-cirrhosis. Aberrant amino acid biosynthesis may be the hallmark with increasing severity of cirrhosis as well as alterations in energetic metabolism.

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Section: Introductionmentioning

confidence: 99%

Serum Metabolic Profiling of Advanced Cirrhosis Based on HCV

et al. 2017

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“…Another unsupervised method for this purpose is the Hierarchical Cluster Analysis (HCA) (8,44). The most used supervised classification methods are k-nearest-Neighbors (kNN) (1,38), Soft Indipendent Modeling of Class Analogy (SIMCA) (12) and Partial Last Squares Discriminant Analysis (PLS-DA) (3,14). The supervised method use the sample class as a variable for establish discrimination rules.…”

Section: Chemometrics (Statistical Analysis)mentioning

confidence: 99%

The omics era: what can nuclear magnetic resonance tell us on metabolomics?

2018

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A brief overview of the potentiality and use of the metabolic fingerprint of a system or biological process is here proposed. The information on the type, quantity and variation of the pool of metabolites and its relationship with a given biological process is commonly referred to as metabolomics. One powerful analytical approach to the detection and quantitation of metabolites is by Nuclear Magnetic Resonance Spectroscopy (NMR). Additionally, the recently introduced High Resolution Magic Angle Spinning (HR-MAS) NMR approach improved dramatically the potentiality of the method allowing direct sampling of ex vivo specimens, such as tissues and cells, without any pre-treatment or extraction steps. The NMR data can be processed towards the target or non-target analysis of the metabolites. The former passes through the identification of all the metabolites, the latter adopts a multivariate statistical approach such as Principal Components Analysis. In this article, the main methodological points of NMR analysis with multivariate statistics are briefly outlined and discussed. A final case-study on the discrimination of healthy and neoplastic tissues via HR-MAS NMR metabolomics is reported as a paradigmatic application.

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“…This technology enables the measurement of various metabolites present in all organisms and provides new risk markers of T2DM and clinical efficacy by indicating the overall drug response index [16][17][18]. Identification of small molecular metabolites in bodily fluids will enable determination of drug effectiveness and prediction of treatment according to the phenotype of patients.…”

Section: Introductionmentioning

confidence: 99%

Mechanism by which Metformin Influence Metabolic Changes in Human: A Systematic-Review

Park¹,

Kim²,

Shin³

2016

J Diabetes Metab

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Metformin is the most widely used oral antihyperglycemic agent for the improvement of type 2 diabetes mellitus (T2DM). In patients with T2DM, metformin increases insulin sensitivity and reduces glucose production. In this systematic review, we identified and compared metabolic changes induced by metformin administration.We searched articles published within the past 5 years on Pubmed.gov by using the keywords "metformin and metabolomics." No restrictions were placed on the languages, species, or gender during the selection of articles. From the 29 identified articles, we excluded non-human in vivo or in vitro studies, studies in cancer patients, and studies in which the focus was not on variation in the levels of metabolites after administration of medication such as pharmacogenetic studies. Finally, we selected 8 articles and compared their results.In the selected study results, a treatment with metformin and a combination of metformin and other anti-diabetic agents decreased the levels of phenylalanine, tyrosine, lysine, and glutamate to 5.58 ± 2.23%, 11.50 ± 2.12%, 25.28 ± 27.90%, and 35.49 ± 26.18% (mean ± SD), respectively, but increased the levels of alanine to 16.00% in 3 months-5 years of follow-up after metformin treatment compared to the control. The levels of total cholesterol and low-density lipoprotein (LDL) cholesterol (5.28%) decreased, whereas those of high-density lipoprotein (HDL) cholesterol increased by 34.65% in 18-30 months of follow-up after administration of metformin.Metformin administration in human alters the blood concentration of phenylalanine, tyrosine, glutamate and lysine. Further confirmatory studies are required to understand how these metabolites related to the drug mechanism and also drug response, and to develop the biomarkers for predicting metformin response in humans.

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Metabolomics and Diabetes: Analytical and Computational Approaches

Cited by 145 publications

References 136 publications

Serum Metabolic Profiling of Advanced Cirrhosis Based on HCV

Serum Metabolic Profiling of Advanced Cirrhosis Based on HCV

The omics era: what can nuclear magnetic resonance tell us on metabolomics?

Mechanism by which Metformin Influence Metabolic Changes in Human: A Systematic-Review

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