Rapid, Non-Invasive Method Diagnoses Type 2 Diabetes by Sniffing Urinary Acetone

By LabMedica International staff writers
Posted on 22 Mar 2023

Over 90% of diabetes cases are attributed to Type 2 diabetes (T2D), a prevalent metabolic condition that is expected to impact 380 million individuals globally by 2025. Despite being highly accurate, the existing diagnostic tests for T2D based on fasting plasma glucose (FPG), oral glucose tolerance test (OGTT) and glycosylated hemoglobin A1c (HbA1c) rely on invasive blood detection. Now, a research team working on a new non-invasive screening method for T2D has used self-developed proton transfer reaction-mass spectrometry (PTR-MS) to detect volatile organic compounds (VOCs) in T2D patients' urine samples.

The research by investigators from the Institute of Health and Medical Technology, Hefei Institutes of Physical Science of the Chinese Academy of Sciences (CAS, Anhui, China) was based on sniffing urinary acetone by PTR-MS. Acetone in urine is one of the ketones produced by fat metabolism. As T2D patients experience insufficient glucose utilization and storage in their blood, their bodies accelerate the metabolism of urinary acetone. In the multicenter study involving 180 T2D patients and 180 healthy individuals, a diagnostic model with an accuracy of 81.3% (sensitivity: 73.3%, specificity: 89.3%) was established by using urinary acetone at center 1, and a threshold of 690.1 ppbv was obtained. The model was subsequently validated in the other two participating centers, yielding similar results. Moreover, the diagnostic accuracy of this approach was found to be on par with the diagnostic method used in the clinic.


Image: Brief schematic diagram of the detection principle and method (Photo courtesy of CAS)

"Sniffing T2D through urinary acetone is safe, non-invasive, fast, and accurate," said XU Wei, first author of the paper. "We hope that the method can provide reference for screening and diagnosis of T2D."

Related Links:
Hefei Institutes of Physical Science, CAS


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