Identification of prognostic and diagnostic biomarkers of glucose intolerance in ApoE3Leiden mice
Open Access
- 1 March 2012
- journal article
- Published by American Physiological Society in Physiological Genomics
- Vol. 44 (5), 293-304
- https://doi.org/10.1152/physiolgenomics.00072.2011
Abstract
The prevalence of diabetes mellitus Type 2 could be significantly reduced by early identification of subjects at risk, allowing for better prevention and earlier treatment. Glucose intolerance (GI) is a hallmark of the prediabetic stage. This study aims at identifying 1) prognostic biomarkers predicting the risk of developing GI later in life and 2) diagnostic biomarkers reflecting the degree of already manifest GI. To this end, disease development was followed over time in mice, and biomarkers were identified using lipidomics and transcriptomics. Young adult ApoE3Leiden mice were treated a high-fat diet for 12 wk to induce GI. Blood was collected before and during disease development. The individual extent of GI was determined with a glucose tolerance test and the area under the curve (AUC) was calculated for each animal. Subject-specific AUC values were correlated to the plasma lipidome (t = 0) and the white blood cell (WBC) transcriptome (t = 0, 6, and 12 wk) to identify prognostic and diagnostic biomarkers, respectively. The plasma ratio of specific free fatty acids prior to high-fat feeding (C16:1/C16:0, C18:1/C18:0 and C18:2/C22:6) was significantly correlated with the AUC and predictive for future GI. Subsequently, the expression level of specific WBC genes (Acss2, Arfgap1, Tfrc, Cox6b2, Barhl2, Abcb4, Cyp4b1, Sars2, Fgf16, and Tceal8) reflected the individual degree of GI during disease progression. Specific plasma free fatty acids as well as their ratio can be used to predict future GI. The expression levels of specific WBC genes can serve as easy accessible markers to diagnose and monitor already existing GI.Keywords
This publication has 49 references indexed in Scilit:
- Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humansJCI Insight, 2011
- Metabolite profiles and the risk of developing diabetesNature Medicine, 2011
- A Combined Transcriptomics and Lipidomics Analysis of Subcutaneous, Epididymal and Mesenteric Adipose Tissue Reveals Marked Functional DifferencesPLOS ONE, 2010
- α-Hydroxybutyrate Is an Early Biomarker of Insulin Resistance and Glucose Intolerance in a Nondiabetic PopulationPLOS ONE, 2010
- Time-Resolved and Tissue-Specific Systems Analysis of the Pathogenesis of Insulin ResistancePLOS ONE, 2010
- MIF Deficiency Reduces Chronic Inflammation in White Adipose Tissue and Impairs the Development of Insulin Resistance, Glucose Intolerance, and Associated Atherosclerotic DiseaseCirculation Research, 2009
- NuGO contributions to GenePatternGenes & Nutrition, 2008
- Identification of a Lipokine, a Lipid Hormone Linking Adipose Tissue to Systemic MetabolismCell, 2008
- The Art and Practice of Systems Biology in Medicine: Mapping Patterns of RelationshipsJournal of Proteome Research, 2007
- Atherosclerosis and liver inflammation induced by increased dietary cholesterol intake: a combined transcriptomics and metabolomics analysisGenome Biology, 2007