Metabolic fingerprint of Gestational Diabetes Mellitus

Dudzik, Danuta; Żórawski, Marcin; Skotnicki, M; Zarzycki, W; Kozłowska, Gabryela; Bibik-Malinowska, Katarzyna; Vallejo, María S.; Garcı́a, Antonia; Barbas, Coral; Ramos, M. Teresa

doi:10.1016/j.jprot.2014.03.025

Cited by 121 publications

(148 citation statements)

References 52 publications

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“…Not surprisingly, metabolomic analyses in GDM have identified signatures similar to other insulin resistant states, including elevations in NEFA and ketones (109–114). Elevations in FA, cholesterol, and lipoproteins may precede and predict GDM (115).…”

Section: The Lipid Metabolomementioning

confidence: 99%

What Have Metabolomics Approaches Taught Us About Type 2 Diabetes?

et al. 2016

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Type 2 diabetes (T2D) is increasing worldwide, making identification of biomarkers for detection, staging, and effective prevention strategies an especially critical scientific and medical goal. Fortunately, advances in metabolomics techniques, together with improvements in bioinformatics and mathematical modeling approaches, have provided the scientific community with new tools to describe the T2D metabolome. Among the metabolomics signatures associated with T2D and obesity include increased levels of lactate, glycolytic intermediates, branched-chain and aromatic amino acids, and long-chain fatty acids. Conversely, tricarboxylic acid cycle intermediates, betaine and other metabolites decrease. Future studies will be required to fully integrate these and other findings into our understanding of the diabetes pathophysiology and to identify biomarkers of disease risk, stage, and responsiveness to specific treatments.

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Section: The Lipid Metabolomementioning

confidence: 99%

What Have Metabolomics Approaches Taught Us About Type 2 Diabetes?

et al. 2016

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“…Two recent metabolomic studies of normal pregnancy have described widespread metabolic perturbations that extend beyond the traditional boundaries of insulin resistance to encompass pathways including amino acids, lipoproteins and inflammatory markers [3,4]. GDM has also been the focus of some recent metabolomic studies, although to date all have included participants from across the maternal weight spectrum, which is itself known to affect the maternal metabolome [5][6][7][8][9]. None has addressed the metabolome in obese women prior to and at the time of GDM diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Metabolic profiling of gestational diabetes in obese women during pregnancy

et al. 2017

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Aims/hypothesis Antenatal obesity and associated gestational diabetes (GDM) are increasing worldwide. While pre-existing insulin resistance is implicated in GDM in obese women, the responsible metabolic pathways remain poorly described. Our aim was to compare metabolic profiles in blood of obese pregnant women with and without GDM 10 weeks prior to and at the time of diagnosis by OGTT. Methods We investigated 646 women, of whom 198 developed GDM, in this prospective cohort study, a secondary analysis of UK Pregnancies Better Eating and Activity Trial (UPBEAT), a multicentre randomised controlled trial of a complex lifestyle intervention in obese pregnant women. Multivariate regression analyses adjusted for multiple testing, and accounting for appropriate confounders including study intervention, were performed to compare obese women with GDM with obese non-GDM women. We measured 163 analytes in serum, plasma or whole blood, including 147 from a targeted NMR metabolome, at time point 1 (mean gestational age 17 weeks 0 days) and time point 2 (mean gestational age 27 weeks 5 days, at time of OGTT) and compared them between groups. Results Multiple significant differences were observed in women who developed GDM compared with women without GDM (false discovery rate corrected p values <0.05). Most were evident prior to diagnosis. Women with GDM demonstrated raised lipids and lipoprotein constituents in VLDL subclasses, greater triacylglycerol enrichment across lipoprotein particles, higher branched-chain and aromatic amino acids and different fatty acid, ketone body, adipokine, liver and inflammatory marker profiles compared with those without GDM. Conclusions/interpretation Among obese pregnant women, differences in metabolic profile, including exaggerated dyslipidaemia, are evident at least 10 weeks prior to a diagnosis of GDM in the late second trimester.

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“…Metabolomics has already emerged as an important and a fundamental research tool in the investigation of health, disease, clinical biomarker, and drug discovery . Focusing on comprehensive analysis of all the metabolites in a biological system, metabolomics provides a direct signature and sensitive measure of the human phenotype .…”

Section: Introductionmentioning

confidence: 99%

A review of blood sample handling and pre‐processing for metabolomics studies

2017

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Metabolomics has been found to be applicable to a wide range of clinical studies, bringing a new era for improving clinical diagnostics, early disease detection, therapy prediction and treatment efficiency monitoring. A major challenge in metabolomics, particularly untargeted studies, is the extremely diverse and complex nature of biological specimens. Despite great advances in the field there still exist fundamental needs for considering pre-analytical variability that can introduce bias to the subsequent analytical process and decrease the reliability of the results and moreover confound final research outcomes. Many researchers are mainly focused on the instrumental aspects of the biomarker discovery process, and sample related variables sometimes seem to be overlooked. To bridge the gap, critical information and standardized protocols regarding experimental design and sample handling and pre-processing are highly desired. Characterization of a range variation among sample collection methods is necessary to prevent results misinterpretation and to ensure that observed differences are not due to an experimental bias caused by inconsistencies in sample processing. Herein, a systematic discussion of pre-analytical variables affecting metabolomics studies based on blood derived samples is performed. Furthermore, we provide a set of recommendations concerning experimental design, collection, pre-processing procedures and storage conditions as a practical review that can guide and serve for the standardization of protocols and reduction of undesirable variation.

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Metabolic fingerprint of Gestational Diabetes Mellitus

Cited by 121 publications

References 52 publications

What Have Metabolomics Approaches Taught Us About Type 2 Diabetes?

What Have Metabolomics Approaches Taught Us About Type 2 Diabetes?

Metabolic profiling of gestational diabetes in obese women during pregnancy

A review of blood sample handling and pre‐processing for metabolomics studies

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