Non-invasive 13C-glucose breath test using residual gas analyzer-mass spectrometry: a novel tool for screening individuals with pre-diabetes and type 2 diabetes

We report, for the first time, the clinical feasibility of a novel residual gas analyzer mass spectrometry (RGA-MS) method for accurate evaluation of the C-13-glucose breath test (C-13-GBT) in the diagnosis of pre-diabetes (PD) and type 2 diabetes mellitus (T2D). In T2D or PD, glucose uptake is impaired and results in blunted isotope enriched (CO2)-C-13 production in exhaled breath samples. Using the Receiver operating characteristics (ROC) curve analysis, an optimal diagnostic cut-off point of the (CO2)-C-13/(CO2)-C-12 isotope ratios expressed as the delta-over-baseline (DOB) value, was determined to be delta(DOB) C-13 parts per thousand = 28.81 parts per thousand for screening individuals with non-diabetes controls (NDC) and pre-diabetes (PD), corresponding to a sensitivity of 100% and specificity of 94.4%. We also determined another optimal diagnostic cut-off point of delta(DOB) C-13 parts per thousand = 19.88 parts per thousand between individuals with PD and T2D, which exhibited 100% sensitivity and 95.5% specificity. Our RGA-MS methodology for the C-13-GBT also manifested a typical diagnostic positive and negative predictive value of 96% and 100%, respectively. The diagnostic accuracy, precision and validity of the results were also confirmed by high-resolution optical cavity enhanced integrated cavity output spectroscopy (ICOS) measurements. The delta(DOB) C-13 parts per thousand values measured with RGA-MS method, correlated favourably (R-2 = 0.979) with those determined by the laser based ICOS method. Moreover, we observed that the effects of endogenous CO2 production related to basal metabolic rates in individuals were statistically insignificant (p = 0.37 and 0.73) on the diagnostic accuracy. Our findings suggest that the RGA-MS is a valid and sufficiently robust method for the C-13-GBT which may serve as an alternative non-invasive point-of-care diagnostic tool for routine clinical practices as well as for large-scale diabetes screening purposes in real-time.