Paving the way for prediabetes diagnostics: biomarkers that reflect impaired glucose tolerance

In 2014, the global prevalence of diabetes was estimated to be at nine percent among adults age 18 and over, with approximately 1.5 million deaths directly attributed to the disease. Furthermore, the World Health Organization (WHO) estimates that by 2030, diabetes will be the seventh-leading cause of death worldwide.^1,2 Type 2 diabetes (T2D) has become a worldwide pandemic that continues unabated, and there remains a great public health need for biomarkers that can detect early signs of the disease (prediabetes) so that those at greatest risk can implement lifestyle changes that delay or prevent the disease.

Prediabetes is currently defined using one or more glycemic-based criteria, including fasting plasma glucose (FPG, 100-125 mg/dL), hemoglobin A1c (A1c, 5.7 percent to 6.4 percent) and two-hour plasma glucose (2hPG, 140-199 mg/dL).³ Unfortunately, these criteria have been shown to identify only partial overlapping groups of subjects and likely reflect different pathophysiological states along the metabolic continuum leading to T2D. In order to complement the diagnosis of prediabetic states such as impaired glucose tolerance, it is necessary to identify and quantify disease-specific biomarkers that provide more information than the currently used glycemic measures.

Impaired glucose tolerance (IGT) is a prediabetic state of hyperglycemia that occurs when blood glucose levels remain high for an extended period after oral ingestion of glucose but not high enough to be diagnosed as T2D. It is associated with insulin resistance, obesity, dyslipidemia (high triglycerides and/or low HDL cholesterol), and hypertension.⁴ Persons with IGT have an increased risk of developing T2D and cardiovascular disease.⁵ It is estimated that 10 percent to 15 percent of adults in the United States have IGT ⁶.

Historically, IGT has been diagnosed via the oral glucose tolerance test (OGTT), with two-hour plasma glucose (2hPG) values of 140-199 mg/dL. The use of the OGTT has diminished considerably in recent years, as it is time-consuming, expensive, and unpopular with both patients and physicians. Due to the greater convenience of measuring FPG and A1c, patients at risk for diabetes are more likely to have these two parameters measured in routine examinations rather than to undergo an OGTT. As a consequence, IGT subjects with normal FPG and A1c may not be identified.

Since glycemic measures alone are insufficient in identifying IGT and the costly OGTT is inconvenient and unpopular, researchers have recently turned to metabolomics to identify IGT-specific biomarkers. For instance, Cobb et al⁷ applied global metabolomic profiling to identify 23 candidate biomarkers from fasting plasma samples taken just prior to an OGTT from a cohort of 1,623 nondiabetic subjects. This work confirmed the idea that multiple metabolic pathways, not directly involved in glucose metabolism, are perturbed in IGT and further demonstrated that metabolites from these perturbed pathways can be used in models predicting IGT.

Two metabolites, α-hydroxybutyric acid (α-HB) and linoleoylplycerophosphocholine (LGPC), performed equally as well as FPG in predicting IGT. Moreover, there were a number of metabolites—including two small organic acids (α-HB and 4-methyl-2-oxopentanoic acid [4MOP]), two lipids (oleic acid and LGPC), a ketone body (ß-hydroxybutyric acid [BHBA]), an amino acid (serine), and a vitamin (pantothenic acid [vitamin B5])—that are complementary with and additive to FPG when utilized in multivariate models for the prediction of IGT. Using a multivariate logistic regression algorithm, a panel of the above metabolites and glucose were measured from 955 fasting plasma samples to predict IGT with a sensitivity of 78 percent and specificity of 72 percent.

The metabolites described in that paper appear to represent a broad sampling of the body’s ability to dispose of a glucose load like that seen in an OGTT from multiple perspectives beyond that of purely glycemic parameters. Global metabolomic approaches to biomarker discovery allow translational research scientists an opportunity to improve upon the status quo, and they are leading to the development of new diagnostics that can significantly improve our ability to identify prediabetic conditions such as insulin resistance and impaired glucose tolerance. Such work will provide clinicians better tools to help identify at-risk patients and ultimately may help individuals to avoid the devastating effects of diabetes by placing more focus on preventive measures.

References

1. WHO. Global status report on noncommunicable diseases 2014. http://apps.who.int/iris/bitstream/10665/148114/1/9789241564854_eng.pdf?ua=1. Accessed January 2, 2016.
2. Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 2006;3(11):e442.
3. American Diabetes Association. Standards of medical care in diabetes—2014. Diabetes Care. 2010:33:2077-2083.
4. 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.
   Circulation 2007;116-151157.
5. DeFronzo RA, Abdul-Ghani M. Assessment and treatment of cardiovascular risk in prediabetes: impaired glucose tolerance and impaired fasting glucose. Am. J. Cardiol. 2011;108(3 Suppl):3B-24B.
6. Centers for Disease Control and Prevention. National Diabetes Fact Sheet: National Estimates and General Information on Diabetes and Prediabetes in the United States, 2005. http://ndep.nih.gov/media/2005_National_Diabetes_Fact_Sheet.pdf?redirect=true
7. Cobb J, Eckhart A, Perichon R. A novel test for IGT utilizing metabolite markers of glucose tolerance. Journal of Diabetes Science and Technology. 2015;9(1):69.