Insulin resistance is a critical pathophysiological state underlying several chronic conditions, including type-2 diabetes, cardiovascular disease (CVD), hypertension, and polycystic ovarian syndrome. Insulin resistance is evident when glucose builds up in the bloodstream instead of being absorbed by the body’s cells. It is a result of a diminished response to the hormone insulin at the whole body, organ, or cellular level.
A panel of biomarkers comprised of a small organic acid (α-hydroxybutyric acid (AHB)), 2 lipids (oleic acid and linoleoylglycero-phosphocholine (LGPC)) and insulin assesses insulin resistance with a single fasting blood sample and may have value as an early indicator of risk for the development of prediabetes and type-2 diabetes.1
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 insulin resistance plays in diabetes, and we’ve established best-in-class expertise to detect metabolites reflective of this condition. This panel focuses on metabolites involved in insulin resistance and their metabolic pathways and can be used to track biomarkers and enhance biological understanding across preclinical and clinical research.
The Quantose® IR test score was developed to estimate the value obtained from the hyperinsulinemic euglycemic clamp, the gold standard for determining insulin sensitivity, within a prospective, observational cohort study of 1277 clinically healthy, non- diabetic people recruited from 13 European countries.2 It is the first and only test to be clinically developed and validated using the clamp.
The Insulin Resistance cut-off of 63 was defined by the top tertile of scores from the European study.2 Concentrations of the panel biomarkers are measured by clinical chemistry (insulin) and mass spectrometric (UHPLC-MS/MS) based quantitation and then combined to generate the Quantose® IR Score.
The Quantose® IR Score is based on a linear regression algorithm utilizing the quantitative measures (natural log transformed) of AHB, oleate, LGPC, and insulin and was designed to estimate the natural log of the Mwbm (insulin-induced glucose infusion rate normalized by whole body mass) from the hyperinsulinemic euglycemic clamp procedure.2 Fasting plasma levels of AHB, LGPC, oleate, and insulin individually correlate significantly with Mwbm.2,3 The algorithm score is then converted to the Quantose® IR score within a range of 1 to 120 by an arithmetic calculation where higher scores denote greater Insulin Resistance.
Download Quantose® IR tech sheet
1. Cobb J, Gall W, Adam KP, et al. A novel fasting blood test for insulin resistance and prediabetes. J Diabetes Sci Technol. 2013;7(1):100-110. Published 2013 Jan 1. doi:10.1177/193229681300700112
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. Gall WE, Beebe K, Lawton KA, et al. alpha-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population. PLoS One. 2010;5(5):e10883. Published 2010 May 28. doi:10.1371/journal.pone.0010883
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| LLOQa | |
|---|---|
| Metabolite | EDTA Plasma |
| 2-Hydroxybutyric acid | 0.500 µg/mL |
| Oleic acid | 10.0 µg/mL |
| LGPC | 2.50 µg/mL |
| Insulin | 2 µg/mL |
aLower Limit of Quantitation (LLOQ) varies for each sample type.
LC-MS/MS: Agilent 1290 UHPLC/Sciex QTrap 5500
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| Sample Type | Sample Requirements |
|---|---|
| Fasting EDTA Plasma | ≥ 300µL |
Others on request
Disclaimer: This panel is for Research Use Only and is not to be used for diagnostic purposes.
It is recommended that the Quantose® IR 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® IR measurement demonstrated fluctuations in individual analytes in subjects experiencing active weight loss. Further studies are required to more fully understand potential correlations between active weight loss, Insulin Resistance and the Quantose® IR measurement. In a situation when a patient is experiencing active weight loss, clinicians should interpret the Quantose® IR test results with caution (Metabolon data on file).
| Test Scores | Reference Intervals | ||
|---|---|---|---|
| AHB | 1.92 to 7.37 μg/mL | Oleate | 25.9 to 114 μg/mL |
| LGPC | 7.60 to 25.4 μg/mL | Insulin | 3.13 to 21.3 μU/mL |
Patients with a Quantose® IR Score of 63 or higher are defined as insulin resistant. This cut-off is defined by the top tertile of scores from a study of 1277 hyperinsulinemic glycemic clamp values of clinically healthy, non-diabetic people recruited from 13 European countries.2 Quantose® IR test score reference intervals were established using 456 non-diabetic subjects at risk for diabetes (IFG, IGT Glucose, and/or FINDRISC score > 12).
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 more than 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.
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 treatment for diabetes at all stages. By facilitating 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.
The liver is the single most important regulator of metabolic homeostasis at the organismal level. That makes metabolomics an indispensable tool for capturing an integrative profile of an individual’s liver function. As the incidence of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) continues to rise, researchers and health-care providers can look to Metabolon to provide much-needed non-invasive diagnostic and prognostic indicators as well as a fundamental understanding of pathological processes. The metabolome integrates an individual’s genetic makeup and gene expression profile with nongenetic factors such as diet, environmental exposures, and the microbiome. Therefore layering metabolomic analysis onto genomic and transcriptomic data provides the best opportunity to understand disease.
Heart disease is a leading cause of death worldwide, and there are numerous factors that lead to this and other cardiovascular diseases (CVD). Metabolomics can illuminate cardiovascular disease at multiple levels. In preclinical studies, such as with cardiomyocytes or heart tissue from model organisms, understanding mitochondrial function, energetics, and redox status can drive critical insights into disease mechanisms. In human studies, metabolomics offers the opportunity to account for well-established CVD risk factors such as cholesterol and complex lipids, while simultaneously profiling thousands of other biochemicals in an unbiased fashion to enable the discovery of novel disease mechanisms and biomarkers.
Once you see the full value of metabolomics, the only remaining question is: who does it best? While many laboratories have metabolite profiling or analytical chemistry capabilities, comprehensive metabolomics technologies are extremely rare.
Accurate, unbiased metabolite identification across the entire metabolome introduces signal-to-noise challenges that very few labs are equipped to handle. Also, translating massive quantities of data into actionable information is slow, if not impossible, for most because proper interpretation takes two things that are in short supply: experience and a comprehensive database.
Using our robust platform and visualization tools, our experts are uniquely able to tell you more about your molecule and develop assay panels to help you zero in on the results you need.
Coverage
Ability to interrogate thousands of metabolites across diverse biochemical space, revealing new insights and opportunities
Comparability
Ability to integrate the data from different studies into the same dataset, in different geographies, among different patients over time
Competency
Ability to inform on proper study design, generate high‐quality data, derive biological insights, and make actionable recommendations
Capacity
Ability to process hundreds of thousands of samples quickly and cost‐efficiently to service rapidly growing demand
