Automated Multi-Injection Gas Chromatography-Photoionization Detection (AMI-GC-PID) for Qualitative and Quantitative Determination of Urinary Acetone

Abstract

Acetone is produced from fat metabolism which is increased in diabetic patients due to the disruption of glucose metabolism. Therefore, urinary acetone is expected to be a biomarker for noninvasive diagnosis of diabetes. Although several techniques have been developed for urinary acetone, none meet the clinical needs of automated multi-injection for numerous samples. In this study, we developed automated multi-injection gas chromatography-photoionization detection (AMI-GC-PID) to determine urinary acetone. First, we optimized the sample preprocessing during urine collection and storage before detection and established a standard protocol. The urine was immediately sealed in headspace bottles, stored at 20 °C for 1 h, and equilibrated for 20 min at 80 °C before analysis. Next we evaluated the repeatability of the method and the influence of the urine matrix. The relative standard deviations (RSDs) of the intra-day (nine measurements) and inter-day (three days) measurements were less than 5%. The recovery rate was 97.4% ± 4.6%. AMI-GC-PID was applied to determine urinary acetone in 44 diabetic patients and 29 healthy subjects. The median concentration of urinary acetone was much higher in diabetic patients than in healthy controls (2019 μg/L compared 699 μg/L). The results show that AMI-GC-PID possesses suitable analytical figures of merit for urinary acetone with broad applications in the noninvasive diagnosis of diabetes.

Keywords:

• Automated multi-injection (AMI)
• diabetes
• gas chromatography-photoionization detector (GC-PID)
• urinary acetone

Acknowledgments

The authors thank all volunteers for their involvement.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data will be made available on request.

Additional information

Funding

This research was supported by the National Natural Science Foundation of China [22076190, 21876176, 62171433], the Youth Innovation Promotion Association, CAS, China [2019432], the Research Fund of Anhui Institute of Translational Medicine [2023zhyx-C78], the HFIPS Director’s Fund [BJPY2021B08, YZJJ2022QN45, YZJJZX202009, YZJJ202305-CX], and the Anhui Provincial Key R&D Program [202104d07020003].