Circadian rhythm and time-of-day-effects of (anti)oxidant biomarkers for epidemiological studies

Abstract

Various biomarkers of oxidative stress and redox status have been used in a number of clinical and epidemiological studies related to diseases and conditions that involve disturbances of the redox balance. However, a comprehensive study of diurnal variations of a set of biomarkers has not been conducted so far. Therefore, the aim of this study is to investigate circadian rhythm and time-of-day-effects of a set of frequently used biomarkers of oxidative stress, redox and antioxidant status in serum/plasma. These biomarkers include Reactive Oxygen Metabolites (ROM), Biological Antioxidant Potency (BAP), Total Thiols in Proteins (TTP), high-sensitive C-Reactive Protein (CRP) and Uric Acid (UA). During a 24-hr study, blood sampling was conducted 6 times at 4-hr intervals. The presence of circadian rhythm was analyzed with CircWave analysis, whereas the effect of time was analyzed with Repeated Measures ANOVA (RM-ANOVA). Thereby, the main focus was on the time points in working hours (8, 12 and 16 hr), which are used frequently in practice. Of all investigated biomarkers, only TTP in males demonstrated statistically significant circadian rhythm (p = 0.040). A statistically significant effect between all six time points with RM-ANOVA was observed for ROM, TTP and UA in both genders, and for BAP in females only. No statistically significant differences were observed between the time points 8 hr and 12 hr for any of the biomarkers that were assessed in our study. In conclusion, diurnal variations in some of the studied biomarkers that we demonstrate here should be taken into account when designing and conducting clinical and epidemiological studies. It is advised to standardize the time of sampling with a preference in the morning hours.

Keywords:

• Serum biomarkers
• plasma biomarkers
• oxidative stress
• redox status
• diurnal variation

Acknowledgements

The authors thank the volunteers who participated in this study. The authors also thank Dr. Jeroen Pennings for his help in CircWave statistical analysis and Dr. Linda van Kerkhof for critical reading of the manuscript and useful suggestions.

Disclosure statement

No potential conflict of interest was reported by the author(s).