Paving the way for prediabetes diagnostics: biomarkers that reflect insulin resistance

Feb. 19, 2015

Type 2 diabetes is a chronic disease characterized by reduced sensitivity to insulin in muscle, liver, and adipose tissue, a condition referred to as “insulin resistance.” Insulin resistance develops before the onset of diabetes and is a predictor of the disease. In fact, insulin resistance can be present more than 10 years prior to diabetes and can be seen prior to any changes in glycemic measures.1 Most people with insulin resistance are able to maintain normal glycemic levels by increasing β-cell secretion to compensate for diminished insulin activity. Over time, though, the β-cells of the pancreas may not produce sufficient insulin to compensate for the increased resistance, and this leads to progressive glucose intolerance (prediabetes) and diabetes.

The current gold-standard test for insulin resistance is the hyperinsulinemic euglycemic clamp. This test is impractical for a clinical setting because it is arduous for the patient, time-consuming (takes several hours to complete), and costly. The patient is continually infused with insulin to maintain hyperinsulinemia while also receiving variable levels of glucose. Blood glucose levels are checked frequently, and the glucose infusion rate is adjusted until a steady state is achieved and glucose uptake by all tissues of the body can be calculated. Given these limitations, the hyperinsulinemic euglycemic clamp is reserved for the research setting. 

A simple blood test that can detect insulin resistance prior to the onset of hyperglycemia is needed for clinical practice. Such a test would have an immediate impact on clinical practice by allowing the identification of at-risk patients earlier on the disease continuum. Researchers have turned to the study of metabolomics to address this need.

Metabolomics is the global interrogation of the biochemical components (i.e., small molecular weight biochemicals or metabolites < 1,500 Da) in a biological sample, and the metabolome is a measure of the output of biochemical pathways. The identification of metabolic biomarkers has traditionally relied upon the analysis of individual biochemical levels and, as such, provided only a partial view of the metabolic fingerprint. The promise of metabolomics (and, incidentally, its major challenge) has been to develop a technology that can extract, identify, and quantitate the entire spectrum of small molecules in a biological sample. By interrogating the entire biochemical spectrum of a clinical sample, it is possible to identify meaningful patterns in multi-analyte levels spanning diverse and interrelated metabolic pathways. The ability to interrogate a clinical sample in an “unbiased” manner to gain a complete picture of metabolism sets the stage for biomarker discovery.

While diabetes is defined by dysfunctional carbohydrate metabolism, the disease evolves in a progressive process that also includes changes in lipid and protein metabolism. By applying metabolomics to the discovery of insulin resistance biomarkers, it is possible to extend beyond the boundaries of glycolysis to identify metabolic changes in various pathways such as amino acid and lipid metabolism.

Using a metabolomic approach to screen a large, well-characterized cohort of non-diabetic subjects with a wide spectrum of insulin sensitivity, researchers identified α-hydroxybutyrate (α-HB) as an important biomarker for insulin resistance.2 α-HB is elevated during insulin resistance and is produced by amino acid metabolism (threonine and methionine) and glutathione anabolism (cystathionine pathway). The biomarker may become elevated by at least two mechanisms: a) elevation of oxidative stress leading to an increased demand for glutathione production, and b) elevation of the NADH/NAD+ ratio due to increased lipid oxidation. Both mechanisms are consistent with the metabolic disturbances that are known to exist leading to diabetes.

Linoleoyl-glycerophosphocholine (L-GPC) has also been identified as a biomarker for insulin resistance.3 Unlike α-HB, which is elevated during insulin resistance, L-GPC levels decline. L-GPC is a lysophosphocholine formed by the action of phospholipase A2 in the liver and by lecithin-cholesterolacyltransferase in the circulation. Therefore, adipose tissue insulin resistance leads to elevated free fatty acid (FFA) concentrations. Raised circulating FFA reconstitutes phospholipids from circulating lipids, resulting in a decline of L-GPC. 

Recently, Cobb et al., used fasting blood levels of α-HB, L-GPC, oleate, and insulin to develop a multiple linear regression algorithm that reflects insulin resistance.4 By combining oleate levels, a fatty acid that is elevated during insulin resistance, and insulin levels with α-HB and L-GPC levels into a single algorithm, the investigators were able to show correlation with insulin resistance. Specifically, the clinical test demonstrated an AUC of 0.79 and outperformed other simple measures of insulin resistance such as fasting insulin, fasting glucose, homeostatic model assessment of insulin resistance (HOMA-IR), and body mass index, which are commonly used in place of the gold-standard clamp. 

The above examples demonstrate the advantage of global technologies such as metabolomics in the discovery of biomarkers. This is particularly true in the case of diabetes, which is a complex metabolic disease involving multiple pathways.

The American Diabetes Association estimates that more than 29 million Americans have diabetes and that the cost of this disease has risen from $174 billion in 2007 to $245 billion in 2012. Research aimed at better understanding the metabolic disturbances underlying diabetes is paving the way for advanced diagnostics. New biomarkers will identify individuals at risk for disease earlier than current glycolysis-based tests and provide a more comprehensive picture that may allow personalized approaches to therapy.

As clinical laboratories look to advancements in next-generation DNA sequencing and proteomics to expand test menus, we should not lose sight of the unique and critical role that biochemical analysis of metabolism plays in the assessment of health and disease. Advanced technologies in nuclear magnetic resonance spectroscopy and mass spectrometry have created renewed interest in metabolism and the unique metabolic fingerprints of diabetes and other metabolic diseases. Metabolomics is creating opportunities for clinical laboratories to consider the potential of “next-generation” metabolic assays that address unmet needs in innovative and meaningful ways. 


  1. Leahy J, Clark N, Cefalu WT. Medical Management of Diabetes Mellitus. New York: M. Dekker, 2000.
  2. 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:el10883.
  3. Ferrannini E, Natali A, Camastra S, et al. Early metabolic markers of the development of dysglycemia and type 2 diabetes and their physiological significance. Diabetes. 2013;63:1730.
  4. Cobb J, Gall W, Adam KP. A novel fasting blood test for insulin resistance and prediabetes. J Diabetes Science and Technology. 2013;1:100.

 Diabetes:  new guidelines for Asian Americans

The American Diabetes Association (ADA) is lowering the Body Mass Index (BMI) cut point at which it recommends screening Asian Americans for type 2 diabetes, aligning its guidelines with evidence that many Asian Americans develop the disease at lower BMI levels than the population at large. The new recommendation appears in a position statement recently published in Diabetes Care.

“The position statement highlights, for the first time, the physiologic differences seen between Asian Americans and other populations affected by diabetes,” says Jane Chiang, the Association’s Senior Vice President for Medical Affairs and Community Information. “Asian Americans are a heterogeneous group and have historically been underrepresented in studies, so it is important to keep in mind that this is just the beginning. Clearly, we need more research to better understand why these distinctions exist.”

For members of the general population, the Association recommends testing for diabetes when BMI reaches 25 kg/m2 or higher. Based upon an exhaustive review of the literature, it is now recommending that for Asian Americans screening be done at 23 kg/m2 or higher. It is believed that Asian Americans develop diabetes at lower BMI levels because of differences in their body composition: weight gain tends to accumulate around the waist in Asian Americans, rather than in other parts of the body. The waist is the area in which adiposity is considered most harmful from a disease standpoint.

“Clinicians have known this intuitively for quite some time,” says William C. Hsu, MD, Vice President, International Programs, Joslin Diabetes Center, and Assistant Professor, Harvard Medical School, who was lead author of the position paper. “They can see that Asian Americans are being diagnosed with diabetes when they do not appear to be overweight or obese according to general standards. But if you use the previous Association standard for diabetes screening of being age 45 or older with a BMI of 25 kg/m2 or above, you will miss many Asian Americans who are at risk

“Given that established BMI cut points indicating elevated diabetes risk are inappropriate for Asian Americans, establishing a specific BMI cut point to identify Asian Americans with or at risk for future diabetes would be beneficial to the potential health of millions of Asian American individuals,” the position statement concludes.

The Asian Americans Native Hawaiian and Pacific Islander (AANHPI) Diabetes Coalition began drawing attention to the need for changes in clinical management guidelines for Asian Americans, who experience twice the prevalence of type 2 diabetes than Caucasian Americans despite having lower rates of obesity under current federal BMI standards, following a 2011 State of the Science Scientific Symposium on Diabetes in Hawaii.

“A thin Asian person may be at risk for developing diabetes. Research has shown that BMI may not be the best marker in this population. This paper is a significant step in the right direction of widely recognizing the diabetes disparity that exists in our populations and communities,” says Ho Luong Tran, MD, President of the National Council of Asian Pacific Islander Physicians. “The next steps are to increase the amount of clinical research and data on this diverse population, while simultaneously pushing for policy change that will positively impact health outcomes.”