Metabolite Biometrics for the Differentiation of Individuals

• NCJ Number: 252792
• Author(s): Mindy E. Hair, Adrianna I. Mathis, Erica K. Brunelle, Lenka Halámková, Jan Halámek
• Date Published: January 2018
• Length: 7 pages
• Agencies: NIJ-Sponsored
• Award: Novel concept for fingerprint analysis

Annotation

This study examined whether concentrations of sweat components are person-specific and can be exploited to differentiate individuals based on trace amounts of sweat.

Abstract

Sweat is a biological fluid present on the skin surface of every individual and is known to contain amino acids as well as other low molecular weight compounds. Individuals are inherently different from one another based on certain factors, including, but not limited to, his/her genetic makeup, environment, and lifestyle. As such, the biochemical composition of each person greatly differs. The concentrations of the biochemical content within an individual’s sweat are largely controlled by metabolic processes within the body that fluctuate regularly based on attributes such as age, sex, and activity level. In testing this concept, the current study analyzed three model compounds—lactate, urea, and glutamate. The average absorbance change from each compound in sweat was determined using three separate bioaffinity-based systems: lactate oxidase coupled with horseradish peroxidase (LOx-HRP), urease coupled with glutamate dehydrogenase (UR-GlDH), and glutamate dehydrogenase alone (GlDH). After optimization of a linear dependence for each assay to its respective analyte, analysis was performed on 50 mimicked sweat samples. Additionally, a collection and extraction method was developed and optimized to evaluate authentic sweat samples from the skin surface of 25 individuals. A multivariate analysis of variance (MANOVA) test was performed to demonstrate that these three single-analyte enzymatic assays were effectively used to identify each person in both sample sets. This novel sweat analysis approach is capable of differentiating individuals, without the use of DNA, based on the collective responses from the chosen metabolic compounds in sweat. Applications for this newly developed, noninvasive analysis can include the field of forensic science. in order to differentiate between individuals, as well as the fields of homeland security and cybersecurity for personal authentication via unlocking mechanisms in smart devices that monitor metabolites. Through further development and analysis, this concept also has the potential to be clinically applicable in monitoring the health of individuals based on particular biomarker combinations. (publisher abstract modified)