Diagnostics of impaired glucose tolerance by the direct mass-spectrometric analysis of plasma metabolites

We have investigated the possibility of application of the direct mass-spectrometric analysis of plasma metabolites for diagnostics of impaired glucose tolerance (IGT). The plasma samples obtained from the control group of patients showing no disturbances of carbohydrate metabolism (n=30) and those with IGT (n=20) were treated with methanol to precipitate proteins and the residual fractions were analysed on a quadrupole flight-of-time mass-spectrometer. A total of 230 metabolites were identified the levels of which were attributable to IGT. The accuracy of diagnostics using the mass-spectrometric analysis was 92% (specificity 94%, sensitivity 89%, area under the Roc-curve 0.94, reproducibility 85%). The detected metabolites included endocanabioids, cresol, ornithine, phospholipids, and fatty acids the presence of which was related to the previously described risk factors of diabetes mellitus. It is concluded that the direct spectrometric analysis of plasma metabolites can be used in routine clinical practice as a more rapid and better reproducible alternative method in comparison with the glucose tolerance test .

diagnostics, plasma metabolites, mass-spectrometric analysis, impaired glucose tolerance, diabetes mellitus

1. Tabák AG, Herder C, Rathmann W, Brunner EJ, Kivimäki M. Prediabetes: a high-risk state for diabetes development. The Lancet. 2012;379(9833):2279-2290. doi: 10.1016/s0140-6736(12)60283-9

2. Mcdonald GW, Fisher GF, Burnham C. Reproducibility of the oral glucose tolerance test. Diabetes. 1965;14:473–480.

3. Ko GTC, Chan JCN, Woo J, Lau E, Yeung VTF, Chow CC, et al. The Reproducibility and Usefulness of the Oral Glucose Tolerance Test in Screening for Diabetes and other Cardiovascular Risk Factors. Annals of Clinical Biochemistry: An international journal of biochemistry and laboratory medicine. 1998;35(1):62-67. doi: 10.1177/000456329803500107

4. Gowda GAN, Zhang S, Gu H, Asiago V, Shanaiah N, Raftery D. Metabolomics-based methods for early disease diagnostics. Expert Review of Molecular Diagnostics. 2008;8(5):617-633. doi: 10.1586/14737159.8.5.617

5. Dettmer K, Aronov PA, Hammock BD. Mass spectrometry-based metabolomics. Mass Spectrometry Reviews. 2007;26(1):51-78. doi: 10.1002/mas.20108

6. Wang TJ, Larson MG, Vasan RS, Cheng S, Rhee EP, McCabe E, et al. Metabolite profiles and the risk of developing diabetes. Nature Medicine. 2011;17(4):448-453. doi: 10.1038/nm.2307

7. Definition and diagnosis of diabetes mellitus and intermediate hyperglycemia. Report of a WHO/IDF Consultation, 2006.

8. Metz CE. Basic principles of ROC analysis. Seminars in Nuclear Medicine. 1978;8(4):283-298. doi: 10.1016/s0001-2998(78)80014-2

9. U.S. Department of Health and Human Services, FDA, CDER, C. Guidance for Industry Bioanalytical Method Validation Guidance for Industry Bioanalytical Method Validation. 2001

10. Crews B, Wikoff WR, Patti GJ, Woo H-K, Kalisiak E, Heideker J, et al. Variability Analysis of Human Plasma and Cerebral Spinal Fluid Reveals Statistical Significance of Changes in Mass Spectrometry-Based Metabolomics Data. Analytical Chemistry. 2009;81(20):8538-8544. doi: 10.1021/ac9014947

11. Strathmann FG, Hoofnagle AN. Current and Future Applications of Mass Spectrometry to the Clinical Laboratory. American Journal of Clinical Pathology. 2011;136(4):609-616. doi: 10.1309/ajcpw0ta8obbngck

12. Engeli S, Bohnke J, Feldpausch M, Gorzelniak K, Janke J, Batkai S, et al. Activation of the Peripheral Endocannabinoid System in Human Obesity. Diabetes. 2005;54(10):2838-2843. doi: 10.2337/diabetes.54.10.2838

13. Sipe JC, Waalen J, Gerber A, Beutler E. Overweight and obesity associated with a missense polymorphism in fatty acid amide hydrolase (FAAH). International Journal of Obesity. 2005;29(7):755-759. doi: 10.1038/sj.ijo.0802954

14. Fonseca VA. The metabolic syndrome,hyperlipidemia, and insulin resistance. Clinical Cornerstone. 2005;7(2-3):61-72. doi: 10.1016/s1098-3597(05)80069-9

15. Breant B, Suhre K, Meisinger C, Döring A, Altmaier E, Belcredi P, et al. Metabolic Footprint of Diabetes: A Multiplatform Metabolomics Study in an Epidemiological Setting. PloS One. 2010;5(11):e13953. doi: 10.1371/journal.pone.0013953

16. Inouye M, Mio T, Sumino K. Dicarboxylic acids as markers of fatty acid peroxidation in diabetes. Atherosclerosis. 2000;148(1):197-202. doi: 10.1016/s0021-9150(99)00263-4

17. Bandyopadhyay GK. Increased Malonyl-CoA Levels in Muscle From Obese and Type 2 Diabetic Subjects Lead to Decreased Fatty Acid Oxidation and Increased Lipogenesis; Thiazolidinedione Treatment Reverses These Defects. Diabetes. 2006;55(8):2277-2285. doi: 10.2337/db06-0062

18. Meijers BKI, Bammens B, De Moor B, Verbeke K, Vanrenterghem Y, Evenepoel P. Free p-cresol is associated with cardiovascular disease in hemodialysis patients. Kidney International. 2008;73(10):1174-1180. doi: 10.1038/ki.2008.31

19. Kashyap SR, Lara A, Zhang R, Park YM, DeFronzo RA. Insulin Reduces Plasma Arginase Activity in Type 2 Diabetic Patients. Diabetes Care. 2007;31(1):134-139. doi: 10.2337/dc07-1198

20. Kitabchi AE, Umpierrez GE, Miles JM, Fisher JN. Hyperglycemic Crises in Adult Patients With Diabetes. Diabetes Care. 2009;32(7):1335-1343. doi: 10.2337/dc09-9032