News05.09.2018Publication of the article “Untargeted Profiling of Concordant/Discordant Phenotypes of High Insulin Resistance and Obesity To Predict the Risk of Developing Diabetes” |
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PhD. Olga Jáuregui, technician of the Separative Techniques technology of the CCiTUB, has participated in the article: “Untargeted Profiling of Concordant/Discordant Phenotypes of High Insulin Resistance and Obesity To Predict the Risk of Developing Diabetes” which has been published in the Journal of Proteome Research. The summary of the article is: "This study explores the metabolic profiles of concordant/discordant phenotypes of high insulin resistance (IR) and obesity. Through untargeted metabolomics (LC-ESI-QTOF-MS), we analyzed the fasting serum of subjects with high IR and/or obesity (n = 64). An partial least-squares discriminant analysis with orthogonal signal correction followed by univariate statistics and enrichment analysis allowed exploration of these metabolic profiles. A multivariate regression method (LASSO) was used for variable selection and a predictive biomarker model to identify subjects with high IR regardless of obesity was built. Adrenic acid and a dyglyceride (DG) were shared by high IR and obesity. Uric and margaric acids, 14 DGs, ketocholesterol, and hydroxycorticosterone were unique to high IR, while arachidonic, hydroxyeicosatetraenoic (HETE), palmitoleic, triHETE, and glycocholic acids, HETE lactone, leukotriene B4, and two glutamyl-peptides to obesity. DGs and adrenic acid differed in concordant/discordant phenotypes, thereby revealing protective mechanisms against high IR also in obesity. A biomarker model formed by DGs, uric and adrenic acids presented a high predictive power to identify subjects with high IR [AUC 80.1% (68.9–91.4)]. These findings could become relevant for diabetes risk detection and unveil new potential targets in therapeutic treatments of IR, diabetes, and obesity. An independent validated cohort is needed to confirm these results." More information about the article in question is available at the following link:[+]. |
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