Novel Algorithms for Comprehensive Untargeted Detection of Doping Agents in Biological Samples.

To address the limitations of current targeted analytical methods that can only detect known doping agents, a novel methodology that permits untargeted drug detection (UDD) has been developed to help in the fight against doping in sports. Fifty-seven drugs were spiked into blank equine plasma and were treated as unknowns since their exact masses and chromatographic retention times were not utilized for detection. The spiked drugs were extracted from the plasma samples and were analyzed using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). The acquired LC-HRMS raw data files were processed using metabolomic software for compound detection and identification. For UDD with the resultant data, a mathematical model was created, and two algorithms were generated to calculate the ratio of the mean (ROM) and outlier index (OLI). Using ROM and OLI, the majority of the 57 drugs were accurately detected by name (52 of 57) or chemical formula (1 of 57). The limit of detection for the drugs was from tens of picograms to nanograms per milliliter. Xenobiotics and endogenous substances relevant to doping control were also identified using this untargeted approach following their extraction from real-world race samples, thus validating the UDD methodology. To the authors' knowledge, this is the first completely UDD methodological approach and represents significant advance toward using artificial intelligence for the detection of both known and emerging doping agents in sports.

Factors affecting untargeted detection of doping agents in biological samples.

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.

Automated identification of unknown doping agents in confiscation samples by flow-injection mass spectrometry and mass spectral library searches.

Rapid and accurate identification of unknown compounds within suspicious samples confiscated for sports doping control and law enforcement drug testing is critical, but such analyses are often conducted manually and can be time-consuming. Here, we report a methodology for automated identification of unknown substances in confiscation samples by rapid automatic flow-injection analysis on a liquid chromatography coupled to high-resolution mass spectrometry system and identifying unknown compounds with Compound Discoverer software. The developed methodology was validated by comparing the automated identification results with those obtained from manual syringe-infusion experiments and manual tandem mass spectral library searches. The automated methodology resulted in far higher throughput and remarkably shorter turnaround time for analysis when compared with manual procedures and, in most cases, yielded more compounds. As this is the first such report to the authors' knowledge, this methodology may potentially transform analysis of confiscated samples in sports doping control and law enforcement drug testing.

Identification of ex vivo catabolites of peptides with doping potential in equine plasma by HILIC-HRMS.

Bioactive peptides pose a great threat to sports integrity. The detection of these peptides is essential for enforcing their prohibition in sports. Identifying the catabolites of these peptides that are formed ex vivo in plasma may improve their detection. In the present study, the stability of 27 bioactive peptides with protection at both termini in equine plasma was examined under different incubation conditions, using HILIC coupled to HRMS. Of the 27 peptides, 13 were stable after incubation at 37°C for 72 hr, but the remaining 14 were less stable. Ex vivo catabolites of these 14 peptides were detected using their theoretical masses generated in silico, their appearance was monitored over the time course of incubation, and their identity was verified by their product ion spectra. Catabolites identified for chemotactic peptide, DALDA, dmtDALDA, deltorphins I and II, Hyp6 -dermorphin, Lys7 -dermorphin, and dermorphin analog are novel. A d-amino acid residue at position 2 or 1 of a peptide or next to its C-terminus protected the relevant terminal from degradation by exopeptidases, but such a residue at position 3 did not. A pGlu residue or N-methylation at the N-terminus of a peptide did not protect its N-terminal. Ethylamide at the C-terminus of a peptide provided the C-terminal protection from attacks by carboxypeptidases. The C-terminal Lys amide in DALDA, dmtDALDA, and Lys7 -dermorphin was susceptible to cleavage by plasma enzymes, which is the first report, to the authors' knowledge. The results from the present study provide insights into the stability of peptides in plasma.