Diurnal and daily fluctuations in levels of the urinary oxidative stress marker 8-hydroxyguanosine in spot urine samples.

Background: Urinary 8-hydroxyguanosine (8-OHGuo) levels serve as a biomarker for oxidative stress and hydroxyl radical-induced RNA damage. Evaluating the diurnal and daily fluctuations in urinary 8-OHGuo excretion levels is essential for understanding its implications. However, research in this area remains limited. In this study, we aim to investigate the diurnal and daily fluctuations in 8-OHGuo levels as well as the factors that influence these variations, using spot urine samples.

Methods: Urine samples were collected from seven healthy participants during each urination from the time of awakening until 24:00 h to evaluate diurnal variations. To assess daily fluctuations, urine samples were collected from 18 healthy participants at the time of awakening for 23 consecutive days. The urinary 8-OHGuo levels were measured using an HPLC-ECD method.

Results: No significant variations were observed in the diurnal levels of urinary 8-OHGuo among non-smokers. Conversely, the daily variation of 8-OHGuo in the urine of the smoker was significant, with a coefficient of variation of 18.71%. Each individual maintained a characteristic value despite some diurnal fluctuations. Furthermore, the daily levels of 8-OHGuo exhibited a range of variations influenced by lifestyle factors, including mental state, sleep duration, smoking, menstrual cycle, and dietary habits.

Conclusion: As a specific marker of RNA oxidation, 8-OHGuo provides unique insights distinct from those provided by the widely used DNA oxidation marker 8-hydroxydeoxyguanosine as an indicator of oxidative stress. Urinary 8-OHGuo could serve as a valuable biomarker for managing and preventing oxidative stress-related diseases, provided that the specific range of daily variations is established. The high daily variation in urinary 8-OHGuo levels necessitates the use of multiple samples to accurately determine individual levels. However, further research with large sample sizes will help to validate these findings.