#AI reads Urine# Two-Step Solid-Phase Extraction Method for Urinary Nucleic Acid Adductomics

Published 11 May, 2025

Nucleic acid damage, caused by various endogenous and exogenous exposures throughout an individual's lifespan, can lead to the formation of adducts, which are closely associated with the development of many diseases. Urine, containing excreted nucleic acid adducts after repair processes, serves as an ideal non-invasive matrix for studying the overall nucleic acid adductome. However, analyzing these adducts in urine is challenging due to matrix interference and the diverse chemical nature of adducts.

In the study, the results indicated that no single SPE column could recover the entire range of standards effectively. The combination of the ENV and PHE columns showed the best adduct recoveries, with 18 out of 20 standards being recovered. Although matrix effects were present, they were within acceptable limits. The analysis of urine samples over three weeks demonstrated the reproducibility of the HRMS and SPE methods. Isotopically labeled standards successfully identified their unlabeled counterparts in urine. In the characterization of urinary adductomes, a varying number of adducts were detected in male and female mice and humans, and some adducts showed significant differences between the two genders.

In conclusion, the two-step SPE method, especially the combination of ENV and PHE cartridges, was highly effective in enriching urinary nucleic acid adducts. Performing untargeted analysis of the urinary nucleic acid adductome provides a valuable non-invasive means to assess the body burden of adducts in different species, which is crucial for understanding the impact of the exposome on nucleic acid adduct formation and disease risk.

Biomolecules. 2025 Apr 17;15(4):594. doi: 10.3390/biom15040594.

 

Youhe Gao

Statement: During the preparation of this work the author(s) used Doubao / AI reading for summarizing the content. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

 

For earlier AI Reads Urine articles:

https://www.keaipublishing.com/en/journals/advances-in-biomarker-sciences-and-technology/ai-reads-urine/

 

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