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Diurnal Variations in Vascular Endothelial Vasodilation Are Influenced by Chronotype in Healthy Humans.

Elise R Facer-Childs | Katie Pake | Vivian Y Lee | Samuel J E Lucas | George M Balanos
Frontiers in physiology | 2019

Introduction: The time of day when cardiovascular events are most likely to occur is thought to be aligned with the circadian rhythm of physiological variables. Chronotype has been shown to influence the time of day when cardiovascular events happen, with early chronotypes reported to be more susceptible in the morning and late chronotypes in the evening. However, no studies have investigated the influence of chronotype on physiological variables responsible for cardiovascular regulation in healthy individuals. Methods: 312 individuals completed the Munich ChronoType Questionnaire to assess chronotype. Twenty participants were randomly selected to continue into the main study. In a repeated-measures experiment, participants were tested between 08:00 and 10:00 h and again between 18:00 and 20:00 h. Measurements of mean arterial pressure, heart rate and vascular endothelial vasodilation via flow-mediated dilatation (FMD) were obtained at each session. Results: Individual diurnal differences in mean arterial pressure and heart rate show no significant relationship with chronotype. Diurnal differences in FMD showed a significant correlation (p = 0.010), driven by a clear significant relationship in the evening and not the morning (p < 0.001). Conclusion: These preliminary data indicate that chronotype influences the diurnal variation of endothelial vasodilation measured using flow-mediated dilatation. Furthermore, we show that the influence of chronotype is much stronger in the evening, highlighting an increased susceptibility for later types. These findings are consistent with the diurnal rhythm in cardiovascular events and uncover potential mechanisms of local mediators that may underpin the influence of chronotype in the onset of these events.

Pubmed ID: 31354532

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Associated grants

  • Agency: Biotechnology and Biological Sciences Research Council, United Kingdom
    Id: BB/J014532/1

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RRID:SCR_002798

Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.

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