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. 2011 Jun;300(6):E1166-75.
doi: 10.1152/ajpendo.00634.2010. Epub 2011 Apr 5.

Noninvasive measurement of plasma glucose from exhaled breath in healthy and type 1 diabetic subjects

Timothy D C Minh  1 , Stacy R Oliver, Jerry Ngo, Rebecca Flores, Jason Midyett, Simone Meinardi, Matthew K Carlson, F Sherwood Rowland, Donald R Blake, Pietro R Galassetti
Affiliations

Noninvasive measurement of plasma glucose from exhaled breath in healthy and type 1 diabetic subjects

Timothy D C Minh et al. Am J Physiol Endocrinol Metab. 2011 Jun.

Abstract

Effective management of diabetes mellitus, affecting tens of millions of patients, requires frequent assessment of plasma glucose. Patient compliance for sufficient testing is often reduced by the unpleasantness of current methodologies, which require blood samples and often cause pain and skin callusing. We propose that the analysis of volatile organic compounds (VOCs) in exhaled breath can be used as a novel, alternative, noninvasive means to monitor glycemia in these patients. Seventeen healthy (9 females and 8 males, 28.0 ± 1.0 yr) and eight type 1 diabetic (T1DM) volunteers (5 females and 3 males, 25.8 ± 1.7 yr) were enrolled in a 240-min triphasic intravenous dextrose infusion protocol (baseline, hyperglycemia, euglycemia-hyperinsulinemia). In T1DM patients, insulin was also administered (using differing protocols on 2 repeated visits to separate the effects of insulinemia on breath composition). Exhaled breath and room air samples were collected at 12 time points, and concentrations of ~100 VOCs were determined by gas chromatography and matched with direct plasma glucose measurements. Standard least squares regression was used on several subsets of exhaled gases to generate multilinear models to predict plasma glucose for each subject. Plasma glucose estimates based on two groups of four gases each (cluster A: acetone, methyl nitrate, ethanol, and ethyl benzene; cluster B: 2-pentyl nitrate, propane, methanol, and acetone) displayed very strong correlations with glucose concentrations (0.883 and 0.869 for clusters A and B, respectively) across nearly 300 measurements. Our study demonstrates the feasibility to accurately predict glycemia through exhaled breath analysis over a broad range of clinically relevant concentrations in both healthy and T1DM subjects.

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Figures

Fig. 1.
Fig. 1.
Mean (± SE) glucose and insulin concentrations on healthy subjects (n = 17, 9 females and 8 males) and type 1 diabetic (T1DM) subjects (protocol DM-1: n = 8, 5 females and 3 males; protocol DM-2: n = 5, 2 males and 3 females) during 4 h of controlled induced metabolic fluctuations. Differences between insulin and glucose concentrations across protocols were compared using Student's t-test with Bonferroni correction (†protocol H vs. protocol DM-1, P < 0.05; *protocol DM-1 vs. protocol DM-2, P < 0.05).
Fig. 2.
Fig. 2.
Top: plasma glucose concentrations predicted from cluster A (acetone, methyl nitrate, ethanol, and ethyl benzene) are plotted against measured plasma glucose concentrations. Each dot represents a time point from our 17 study visits by healthy subjects (9 females and 8 males, 28.0 ± 1.0 yr) and 13 study visits by T1DM volunteers (protocol DM-1: n = 8, 5 females and 3 males, 25.8 ± 1.7 yr; protocol DM-2: n = 5, 2 males and 3 females). Bottom: time course overlays of predicted and measured glucose concentrations during a 4-h study visits displayed; the subjects from both healthy and T1DM cohorts with the 2 highest and 2 lowest correlations are presented. Dashed lines represent glucose concentrations predicted by breath gases (incorporating a 15-min time delay), and the solid lines represent plasma measurements from our Beckman Glucose Analyzer II.
Fig. 3.
Fig. 3.
Top: plasma glucose concentrations predicted from cluster B (2-pentyl nitrate, propane, methanol, and acetone) are plotted against measured plasma glucose concentrations. Each dot represents a time point from our 17 study visits by healthy subjects (9 females and 8 males, 28.0 ± 1.0 yr) and 13 study visits by T1DM volunteers (prootcol DM-1: n = 8, 5 females and 3 males, 25.8 ± 1.7 yr; protocol DM-2: n = 5, 2 males and 3 females). Bottom: time course overlays of predicted and measured glucose concentrations during 4-h study visits displayed; the subjects from both healthy and T1DM cohorts with the 2 highest and 2 lowest correlations are presented. Dashed lines represent glucose concentrations predicted by breath gases (incorporating a 15 min time delay), and the solid lines represent plasma measurements from our Beckman Glucose Analyzer II.
Fig. 4.
Fig. 4.
Parkes consensus error grid plot for T1DM (24). Glucose concentrations predicted from clusters A and B were plotted against actual plasma measurements by the Beckman Glucose Analyzer II for all 30 study visits (both healthy and T1DM participants). Zone A represents no effect on clinical action; zone B represents altered clinical action, little or no effect on clinical outcome; zone C represents altered clinical action, likely to affect clinical outcome; zone D represents altered clinical action, could have significant medical risk; and zone E represents altered clinical action, could have dangerous consequences. Using cluster A, 286 of 290 glucose predictions fell into in zone A or B (r = 0.887; left). Using cluster B, 293 of 295 points in zone A or B (r = 0.872; right).
Fig. 5.
Fig. 5.
A variability summary plot of correlation coefficients for glucose predictions from clusters A and B against direct measurements by protocol. The top and bottom lines of each column indicate the maximum and minimum correlation coefficients, and the box indicates the interquartile range and median value.
Fig. 6.
Fig. 6.
A representative time course overlay of glucose and methyl nitrate concentrations for one T1DM subject undergoing protocol DM-2 (r = 0.974) is displayed. In a previous study, we observed methyl nitrate to parallel hyperglycemia in a cohort of T1DM children (22). A weaker correlation was observed in healthy subjects.
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