2013
DOI: 10.1373/clinchem.2013.207993
|View full text |Cite
|
Sign up to set email alerts
|

Diabetes Subphenotypes and Metabolomics: The Key to Discovering Laboratory Markers for Personalized Medicine?

Abstract: For decades, glucose, hemoglobin A 1c , insulin, and C peptide have been the laboratory tests of choice to detect and monitor diabetes (1 ). However, these tests do not identify individuals at risk for developing type 2 diabetes (T2Dm) 4 (so-called prediabetic individuals and the subphenotypes therein), which would be a prerequisite for individualized prevention. Nor are these parameters suitable to identify T2Dm subphenotypes, a prerequisite for individualized therapeutic interventions. The oral glucose toler… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
2
0
2

Year Published

2015
2015
2020
2020

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(4 citation statements)
references
References 14 publications
0
2
0
2
Order By: Relevance
“…Further, this review illustrates the use of metabolomics as a powerful tool for the identification of relevant pattern of hundreds of detected metabolites that could be used to predict future development of T2D. However, metabolic profiles acquired with semi-or non-targeted approaches are complex and required dedicated variable selection to build powerful predictive models of specific prediabetic phenotypes 50 . As the analysis of data is one of the most challenging steps in the metabolomics approach due to high data dimensionality and limited number of samples, recommendations as well as appropriate statistical workflows have been proposed.…”
Section: Metabolites Associated With Mets Clinical Components the Sementioning
confidence: 99%
“…Further, this review illustrates the use of metabolomics as a powerful tool for the identification of relevant pattern of hundreds of detected metabolites that could be used to predict future development of T2D. However, metabolic profiles acquired with semi-or non-targeted approaches are complex and required dedicated variable selection to build powerful predictive models of specific prediabetic phenotypes 50 . As the analysis of data is one of the most challenging steps in the metabolomics approach due to high data dimensionality and limited number of samples, recommendations as well as appropriate statistical workflows have been proposed.…”
Section: Metabolites Associated With Mets Clinical Components the Sementioning
confidence: 99%
“…Untargeted metabolomics continues to expand to exciting life science application domains fuelled by progress in high-resolution liquid chromatography mass spectrometry (LC-MS), bioinformatics tools for data processing, and by recent huge investments (). However, methodological maturity has not yet been reached, thus hindering field’s progress and application to epidemiology .…”
mentioning
confidence: 99%
“…Durante décadas, la glucosa, la hemoglobina A1c, la insulina y el péptido C han sido las pruebas de laboratorio de elección para detectar y vigilar la diabetes. Sin embargo, estas pruebas no identifican a los individuos prediabéticos o sus subfenotipos que están en riesgo de desarrollar DM tipo 2, este sería un requisito para la prevención individualizada (17) .…”
Section: Introductionunclassified
“…Este procedimiento, sin embargo, es muy largo y costoso y no es recomendable como método de cribado en una consulta médica. Por lo tanto, existe la necesidad de pruebas de laboratorio innovadoras para simplificar la detección precoz de las alteraciones en el metabolismo de la glucosa (17) . Las nuevas tecnologías para el diagnóstico, como la metabolómica, son herramientas sensibles, específicas y de gran utilidad frente a otras técnicas modernas, como la genómica.…”
Section: Introductionunclassified