Is genotoxicity a suitable biomarker for monitoring anabolic-androgenic steroids exposure in vivo? A systematic review and meta-analysis.
Thiago Guedes PintoIngra Tais MalacarneWilton Mitsunari TakeshitaMilena de Barros VianaAna Claudia Muniz RennoDaniel Araki RibeiroPublished in: Journal of applied toxicology : JAT (2024)
Steroids stand for a class of hormones (natural and synthetic) known to be helpful for a number of disorders. Despite the aforementioned beneficial effects of using these hormones, anabolic-androgenic steroids (AAS) are also widely abused in a non-therapeutic manner for muscle-building and strength-increasing properties that may lead to genotoxicity in different tissues. The present study aims to understand whether genotoxicity may be a suitable biomarker for AAS exposure in vivo in both experimental animal and human studies. All studies published in PubMed/Medline, Scopus, and Web of Science electronic databases that presented data on DNA damage caused by AAS were analyzed. A total of 15 articles were included in this study, and after thoroughly reviewing the studies, a total of 8 articles were classified as Strong, 6 were classified as Moderate, and only 1 was classified as Weak, totaling 14 studies being considered either Strong or Moderate. This classification makes it possible to consider the present findings as reliable. The meta-analysis data revealed a statistically significant difference in Wistar rat testis cells with AAS compared to control for tail length and % tail DNA (p < 0.001), so that the selected articles were considered homogeneous and the I 2 of 0% indicated low heterogeneity. In summary, genotoxicity can be considered a suitable biomarker for monitoring AAS exposure as a result of DNA breakage and oxidative DNA damage.
Keyphrases
- dna damage
- case control
- systematic review
- oxidative stress
- big data
- endothelial cells
- induced apoptosis
- electronic health record
- dna repair
- circulating tumor
- high intensity
- single molecule
- cell free
- oxide nanoparticles
- meta analyses
- skeletal muscle
- cell proliferation
- cell cycle arrest
- cell death
- signaling pathway
- artificial intelligence
- nucleic acid