Impaired Glucose Tolerance Targeted Panel
Rigorous Quality Control
About Impaired Glucose Tolerance
Impaired Glucose Tolerance is a prediabetic state of hyperglycemia that is associated with insulin resistance and an increased risk of cardiovascular disease.1 The condition occurs when blood glucose levels remain high for an extended period after oral ingestion of glucose but are not high enough to be diagnosed as type 2 diabetes. Impaired Glucose Tolerance can be assessed with a single fasted blood draw by measuring a panel of selected metabolites comprised of two small organic acids (α-hydroxybutyric acid (AHB) and 4-methyl-2-oxopentanoic acid (4MOP)), 2 lipids (oleic acid and linoleoyl glycerophosphocholine (LGPC)), a ketone body (β-hydroxybutyric acid (BHBA)), an amino acid (serine), a vitamin (pantothenic acid (vitamin B5)), and glucose.2
Metabolomics reveals biological insights otherwise unseen. For a successful metabolomics study, both small molecule discovery and the ability to dig deeper into specific biomarkers of interest are needed to uncover actionable insights that propel new therapeutic developments. A specific combination of liquid chromatography-mass spectrometry (LC-MS) technology and biochemical expertise is required to identify these biomarkers of interest and develop assays that are sensitive enough to explore them fully.
At Metabolon, we understand the crucial role glucose tolerance plays in diabetes, and we’ve established best-in-class expertise to assess this condition. This panel focuses on specific metabolites and their pathways that impact glucose tolerance. This panel can be used to track biomarkers and enhance biological understanding across preclinical and clinical research.
Impaired Glucose Tolerance Targeted Panel for Clinical Use—Quantose® IGT
The Quantose® IGT algorithm was developed using fasting samples taken from subjects just prior (time=0) to undergoing an oral glucose tolerance test (OGTT) in the RISC (Relationship between Insulin Resistance and Cardiovascular disease) study 3 year follow up.2 This study was a prospective, observational, cohort study in clinically healthy people at baseline between the ages of 30 and 60 years recruited from 13 European countries.3 Fasting samples from 843 normal glucose tolerant (NGT) and 112 IGT subjects taken at the RISC 3 year follow up were utilized in the algorithm development.
The Impaired Glucose Tolerance cut-off of 60 was defined by the top tertile of scores from the RISC study. Concentrations of the panel biomarkers are measured by clinical chemistry (glucose) and mass spectrometry (UHPLC-MS/MS) based quantitation and then combined to generate the Quantose® IGT Score.
The Quantose® IGT Score is based on a logistic regression algorithm utilizing the quantitative measures of AHB, oleic acid, LGPC, BHBA, 4MOP, serine, vitamin B5 and glucose and was designed to estimate the probability of IGT. Fasting plasma levels of AHB, oleic acid, LGPC, BHBA, 4MOP, serine, vitamin B5, and glucose individually correlate significantly with the 2hPG value from the OGTT. The algorithm score is then converted to the Quantose® IGT score having a range of 1 to 200 by an arithmetic calculation where higher scores denote higher risk of having Impaired Glucose Tolerance.
Impaired Glucose Tolerance Targeted Panel Details
Swipe left/right to view the full table.
|2-Hydroxybutyric acid||0.500 µg/mL|
|4-Methyl-2-oxopentanoic acid||0.500 µg/mL|
|Oleic acid||10.0 µg/mL|
|3-Hydroxybutyric acid||1.00 µg/mL|
*Lower Limit of Quantitation (LLOQ) varies for each sample type.
Analysis Method and Instrumentation:
LC-MS/MS (Agilent 1290 UHPLC/Sciex QTrap 5500)
|Sample Type and Required Amounts|
|Sample Type||Sample Requirements|
|Fasting EDTA Plasma||0.5 mL|
Versions of this panel are available for Research Use Only or Clinical Use.
Clinical Use Panel Interpretive Information
It is recommended that the Quantose® IGT test be administered to patients with relatively stable weight (+/- 3 lbs. over one month) and before and after diet and exercise programs.
In a 12-week, 70 subject study, the Quantose® IGT measurement demonstrated fluctuations in individual analytes in subjects experiencing active weight loss. Further study is required to more fully understand potential correlations between active weight loss and the Quantose® IGT measurement. In a situation when a patient is experiencing active weight loss, clinicians should interpret the Quantose® IGT test results with caution (Metabolon data on file).
|Test Scores||REFERENCE INTERVALS|
|AHB||1.92 to 7.37 μg/mL||Oleic acid||25.9 to 114 μg/mL|
|LGPC||7.60 to 25.4 μg/mL||BHBA*||1.40 to 38.8 μg/mL|
|4MOP||2.60 to 6.20 μg/mL||Serine||7.10 to 14.8 μg/mL|
|Vitamin B5||0.265 to 0.150 μg/mL||Glucose||**|
*The BHBA (beta-hydroxybutyrate) assay in Quantose® IGT has not been validated for the diagnosis of diabetic ketoacidosis. If this condition is suspected, other definitive testing may be considered.
**Normal = <100 mg/dL; Prediabetic = 100 to 125 mg/dL; Diabetic= ≥126 mg/dL4
Patients with a Quantose® IGT Score of 60 or higher are indicative of having impaired glucose tolerance. This cut-off is defined by the top tertile of scores from a study of 955 clinically healthy, non-diabetic people recruited from 13 European countries having a 12% prevalence of IGT.2 Quantose® IGT test score reference intervals were established using 456 non-diabetic subjects at risk for diabetes (IFG, IGT, and/or FINDRISC score > 12).
Delivering Absolute Quantification for Research and Biomarker Analysis
Our readily available or custom developed quantitative assays help you achieve your research and biomarker validation objectives with precise and fully validated methods. Our targeted assays and panels cover >1,000 metabolites and lipids across a wide range of biochemical classes, metabolic pathways, and physiological processes, and they can be customized to best fit any application.
Impaired Glucose Tolerance Targeted Panel Applications
Diabetes is a serious metabolic condition affecting more than 37 million Americans and 460 million people worldwide according to the most recent report from the Centers for Disease Control. Despite being a worldwide epidemic, much remains unknown about individual risk factors for diabetes development, and research is currently being done to identify new and effective treatments for diabetes at all stages. By facilitating the assessment of specific metabolic pathways impacted by diabetes, targeted metabolomics can be a critical tool used to identify biomarkers of disease development for early intervention and novel targets to control disease progression, as well for the development of new pharmaceuticals with specific mechanisms of action.
Big Insights with Metabolon
Cited in over 3,000 publications, we help scientists and manufacturers gain greater insight into their studies through metabolomics. See how our approach can become a successful part of your workflow.
Related Metabolomics Resources
Talk with an expert
Request a quote for our services or more information on sample types and handling procedures, need a letter of support, or simply have questions about how metabolomics can advance your research.
617 Davis Drive, Suite 100
Morrisville, NC 27560
P.O. Box 110407
Research Triangle Park, NC 27709
+1 (919) 572-1711
1. Barr EL, Zimmet PZ, Welborn TA, et al. Risk of cardiovascular and all-cause mortality in individuals with diabetes mellitus, impaired fasting glucose, and impaired glucose tolerance: the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab). Circulation. 2007;116(2):151-157. doi:10.1161/CIRCULATIONAHA.106.685628
2. Cobb J, Eckhart A, Perichon R, et al. A novel test for IGT utilizing metabolite markers of glucose tolerance. J Diabetes Sci Technol. 2015;9(1):69-76. doi:10.1177/1932296814553622
3. Hills SA, Balkau B, Coppack SW, et al. The EGIR-RISC STUDY (The European group for the study of insulin resistance: relationship between insulin sensitivity and cardiovascular disease risk): I. Methodology and objectives. Diabetologia. 2004;47(3):566-570. doi:10.1007/s00125-004-1335-5
4. American Diabetes Associate Standards of Medical Care in Diabetes – 2015. Diabetes Care. 2015; 38(Sup 1):S8-S16