Factors affecting untargeted detection of doping agents in biological samples.
Abstract: Doping control is essential for sports, and untargeted detection of doping agents (UDDA) is the holy grail for anti-doping strategies. The present study examined major factors impacting UDDA with metabolomic data processing, including the use of blank samples, signal-to-noise ratio thresholds, and the minimum chromatographic peak intensity. Contrary to data processing in metabolomics studies, both blank sample use (either blank solvent or plasma) and marking of background compounds were found to be unnecessary for UDDA in biological samples, the first such report to the authors' knowledge. The minimum peak intensity required to detect chromatographic peaks affected the limit of detection (LOD) and data processing time for untargeted detection of 57 drugs spiked into equine plasma. The ratio of the mean (ROM) of the extracted ion chromatographic peak area of a compound in the sample group (SG) to that in the control group (CG) impacted its LOD, and a small ROM value such as 2 is recommended for UDDA. Mathematical modeling of the required signal-to-noise ratio (S/N) for UDDA provided insights into the effect of the number of samples in the SG, the number of positive samples, and the ROM on the required S/N, highlighting the power of mathematics in addressing issues in analytical chemistry. The UDDA method was validated by its successful identification of untargeted doping agents in real-world post-competition equine plasma samples. This advancement in UDDA methodology will be a useful addition to the arsenal of approaches used to combat doping in sports.
Copyright © 2023 Elsevier B.V. All rights reserved.
Publication Date: 2023-03-11 PubMed ID: 36940570DOI: 10.1016/j.talanta.2023.124446Google Scholar: Lookup
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Summary
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This research paper investigates the key factors that influence the untargeted detection of doping agents (UDDA) in biological samples, using metabolomic data processing. It concludes that the use of blank samples and marking of background compounds are not necessary for UDDA in biological samples, while the minimum peak intensity impacts the limit of detection and data processing time. A ratio of the mean of 2 is recommended for UDDA. The paper’s findings apply mathematical modeling to the field of analytical chemistry and anti-doping efforts, and are validated through real-world testing.
Objective and Methodology
- The objective of the study was to explore the main elements affecting the untargeted detection of doping agents using metabolomic data processing.
- Three key factors were examined: the use of blank samples, signal-to-noise ratio thresholds, and the minimum chromatographic peak intensity.
- Contrary to commonly-used data processing in metabolomics studies, the study identifies that marking background compounds and blank sample use are not necessary in UDDA in biological samples.
Findings
- The minimum peak intensity required to detect chromatographic peaks influenced the limit of detection and the data processing time for the untargeted detection of drugs in equine plasma.
- The ratio of the mean (ROM) of an extracted ion chromatographic peak area in a sample group (SG) compared to a control group (CG) also affected its limit of detection. A lower ROM value, such as 2, is recommended for UDDA.
Applications and Insights
- The study applies mathematical modeling to the required signal-to-noise ratio for UDDA, offering insights into the effect of the number of samples in the sample group, the number of positive samples, and the ROM on the required signal-to-noise ratio.
- This research showcases the applicability and importance of mathematical modeling in analytical chemistry and doping control strategies, by providing the first report on the unnecessary use of blank samples and background compounds for UDDA.
Validation and Implication
- The findings were validated through real-world testing, where the UDDA method successfully identified doping agents in post-competition equine plasma samples.
- The improvement in UDDA methodology serves as a useful tool in the arsenal of strategies used to thwart doping in sports.
Cite This Article
APA
Guan F, You Y, Fay S, Adreance MA, McGoldrick LK, Robinson MA.
(2023).
Factors affecting untargeted detection of doping agents in biological samples.
Talanta, 258, 124446.
https://doi.org/10.1016/j.talanta.2023.124446 Publication
Researcher Affiliations
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA. Electronic address: guanf@vet.upenn.edu.
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA.
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA.
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA.
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA.
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA.
MeSH Terms
- Horses
- Animals
- Chromatography, High Pressure Liquid / methods
- Plasma / chemistry
- Limit of Detection
- Metabolomics
- Doping in Sports
Conflict of Interest Statement
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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