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

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BackgroundUrinary 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.MethodsUrine 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.ResultsNo 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.ConclusionAs 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.