| Advances in Doping Detection Technologies: From Traditional to Genomic and Proteomic Innovations |
| Paper ID : 1048-SPORTCONGRESS |
| Authors |
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Amir Amirkhani *1, Farnoosh Berahmand2 1Department of Pharmacology and Toxicology, Faculty of Pharmacy, Kerman University of Medical Sciences, Kerman, Iran 2Student Research Committee Shahid Beheshti University of Medical Sciences |
| Abstract |
| Introduction: Doping in sports, from chemical agents to gene therapy, compromises fair competition and athlete health. This review examines advancements in detection technologies, analyzing over 50 studies from 2020–2025. Traditional methods like gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) offer sensitivities of 0.1–10 ng/mL but struggle with gene doping and designer drugs. Next-generation sequencing (NGS) detects synthetic EPO with 95% specificity, while high-resolution mass spectrometry (HRMS) extends detection windows for growth hormone biomarkers to 2–3 weeks. Multi-omics approaches, integrating genomics, proteomics, and metabolomics, achieve 98% detection rates in spiked samples, enhanced by machine learning to reduce false negatives. Challenges include detecting gene therapy, sample stability, and ethical concerns over genomic data. Future innovations involve AI-driven profiling, non-invasive sampling (e.g., saliva, dried blood spots), and real-time biosensors, aligning with the World Anti-Doping Agency’s mission for doping-free sports. Methods: Doping threatens sports integrity, with the World Anti-Doping Agency (WADA) reporting 1–2% detection rates despite 250,000 annual tests [1]. This review explores technological solutions to address evolving doping methods. Methods: A systematic review of 50+ peer-reviewed articles (2020–2025) from PubMed, Scopus, and WADA reports was conducted, focusing on GC-MS, LC-MS, NGS, HRMS, and multi-omics approaches. Results: GC-MS and LC-MS detect steroids and peptides effectively but fail against gene doping. NGS and CRISPR-based assays identify transgenic signatures, while HRMS quantifies biomarkers like IGF-1. Multi-omics and AI achieve near-perfect detection accuracy. Conclusion: Genomic, proteomic, and multi-omics innovations, supported by AI, revolutionize doping detection. Non-invasive and real-time methods are critical for ensuring fair competition. Keywords: Doping detection, GC-MS, LC-MS, next-generation sequencing, proteomics, gene doping, multi-omics, machine learning Reference: 1.World Anti-Doping Agency. (2023). Annual testing report. https://www.wada-ama.org/en/resources/anti-doping-testing/2023-testing-figures-report 2.World Anti-Doping Agency. (2025). Prohibited list 2025. https://www.wada-ama.org/en/prohibited-list 3. Maurer, H. H. (2002). Role of gas chromatography–mass spectrometry with negative ion chemical ionization in clinical and forensic toxicology, doping control, and biomonitoring. Therapeutic drug monitoring, 24(2), 247-254. 4. de Boer, E. N., van der Wouden, P. E., Johansson, L. F., van Diemen, C. C., & Haisma, H. J. (2019). A next-generation sequencing method for gene doping detection that distinguishes low levels of plasmid DNA against a background of genomic DNA. Gene therapy, 26(7), 338-346. |
| Keywords |
| Doping detection, GC-MS, LC-MS, next-generation sequencing, proteomics, gene doping, multi-omics, machine learning |
| Status: Abstract Accepted (Poster Presentation) |
