Document Type

Article

Publication Date

1-2022

Abstract

Background: Given the utility of the doubly labeled water (DLW) method for determination of energy expenditure, additional techniques for isotope analysis of the samples are welcome. Laser-based instruments are one such new analytical tool, but their accuracy and feasibility for DLW studies are grossly understudied.

Objectives: We assessed the accuracy of laser-based isotope ratio measurements as part of the DLW method for estimation of carbon dioxide production rate (rCO2) and total energy expenditure (TEE), in between-group comparison study designs.

Methods: Urine samples from a previous study were analyzed with a laser-based instrument [off-axis integrated cavity output spectroscopy (OA-ICOS)]. In that study, participants consumed a high-, moderate-, or low-carbohydrate diet for 20 wk; urine samples were obtained in weeks 18–20 before and after a 2H- and 18O-enriched water dose. Isotope ratios (δ2H and δ18O), rCO2, and TEE calculated by standard methods were compared to results previously obtained with the standard technique of isotope ratio mass spectrometry (IRMS). Bias, SD, and bias ± 1.96SD bands between IRMS and OA-ICOS were computed.

Results: The between OA-ICOS and IRMS rCO2 and TEE trends were equivalent (within 1.2% and 4.1%, respectively), in spite of the differences in measured δ18O values at high enrichment levels. The OA-ICOS δ18O values displayed an increasing offset from the IRMS results as the 18O enrichment increased (mean ± SD 4.6–5.7‰ ± 2‰ offset at the time point with highest 18O enrichment, ∼135‰), whereas the hydrogen isotope ratio (δ2H) differed only slightly between the methods (mean offset −4.9‰ for all time points). The between-diet differences in TEE from the previous study were recapitulated with a smaller subset of participants and time points.

Conclusions: OA-ICOS analysis is an accurate and feasible technique for the DLW method. Given the δ18O offset observed at high enrichment, validation of each OA-ICOS instrumental setup against established methods (e.g., IRMS) is recommended.

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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