DOI: 10.5061/dryad.2280gb62w
title: Interstitial cortisol measurements aligned by wake time, healthy volunteers

description: Background: Cortisol is released upon activation of the
 hypothalamic-pituitary-adrenal axis, varies across the day, and possesses
 an underlying diurnal rhythm reactive and responsive to stressors. While
 the endogenous peak of cortisol occurs in the morning, the observed
 cortisol rise post-awakening has been named the cortisol awakening
 response (CAR) based on the belief that the act of waking up stimulates
 cortisol secretion. However, objective evidence that awakening universally
 induces cortisol secretion is limited. Methods: We used a mixed effects
 model with a linear spline fitted to the data to examine tissue free
 cortisol measurements obtained from 201 healthy volunteers by automated
 ambulatory microdialysis before and after awakening in their home
 environments. We also examined rate of change of cortisol depending on
 sleep duration and relative timing. Results: We found no evidence for a
 change in the rate of cortisol increase in the hour after waking when
 compared with the hour prior to waking. We instead observed substantial
 interindividual variability in absolute concentration and rate of change,
 and differences in dynamics that may be attributable to duration and
 relative timing of sleep. Conclusion: Based on these results, we strongly
 suggest caution is needed when interpreting cortisol measurements solely
 obtained in the hour after waking. 
description: This dataset contains serial measurements of cortisol collected
 by ambulatory microdialysis as described in https://doi.org/10.1126/scitranslmed.adg8464 The original data available at https://doi.org/10.18710/5TW8YF have been processed using Python code to realign time series for each participant relative to wake time. There are 5 CSV files containing the following fields: "value" : measurements of cortisol in nmol/L "minutes" : time (in minutes) of the observation relative to wake time "bins" : the 20 minute time range the observation occured within, placeholder only, not used for analysis "SID" : subject identifier - anonymised, identifies each unique participant There is one .R code file: contains code to run mixed linear models using the CSV files in the repository. Version of R and R packages included in the code file
description: # Interstitial cortisol measurements aligned by wake time, healthy
 volunteers
 [https://doi.org/10.5061/dryad.2280gb62w](https://doi.org/10.5061/dryad.2280gb62w) ## Description of the data and file structure The aim of this analysis was to investigate whether waking was associated with an increase in tissue free cortisol in a cohort of night-sleeping healthy volunteers, free from active medical diagnoses or regular medication, and who chose their own sleep period. To do this, we analysed data collected as part of the Dynamic Hormone Diagnostics (ULTRADIAN) observational cohort study (NCT02934399) and available in a public repository (UiB Open Research Data, https://doi.org/10.18710/5TW8YF). The methods of data collection and preparation are described in detail in Upton, Zavala, Methlie et al. (2023) but briefly, involved the use of a portable microdialysis-based sampling system that enabled continuous sampling in subcutaneous tissue. Each participant completed a 24-hour sampling session generating 72 individual samples, representing a 20-minute sampling resolution. During the sampling period participants continued normal activities, and the sleep period occurred in the participant’s own home. Participants were free to select their own sleep and wake times, which were self-reported in an activity diary for both the night prior to and night of sampling. Concentrations of free cortisol and other adrenal steroids were quantified in each sample using liquid chromatography–tandem mass spectrometry. In the dataset, each microdialysis measurement was timestamped as the midpoint of cumulative sample collected over a 20-minute period (for example sample collected between 06:00-06:20 would be labelled 06:10), and then the time of each sample was realigned relative to individual wake time. Since wake time did not necessarily coincide exactly with this midpoint sample time, we included any samples collected within the period of 70 minutes before and after wake time. ### Files and variables #### File: healthy\_cohort\_\_Cortisol\_LME\_R\_n\_201.csv **Description:** Wake-aligned cortisol measurements for the entire cohort, n=201 ##### Variables * : empty * value: microdialysate cortisol concentration, in nmol/L * Minutes: time in minutes, relative to wake time * bins: time bin in which the observation occurred, not used for analysis * SID: unique anonymous participant identified #### File: healthy\_cohort\_longest\_quartile\_Cortisol\_LME\_R\_n\_51.csv **Description:** Subset of cohort with the longest sleep duration (n=51) ##### Variables * : * value: microdialysate cortisol concentration, in nmol/L * Minutes:  time in minutes, relative to wake time * bins: time bin in which the observation occurred, not used for analysis * SID: unique anonymous participant identified #### File: healthy\_cohort\_aligned\_wake\_Cortisol\_LME\_R\_n\_135.csv **Description:** Subset of cohort with aligned wake time (relative to previous morning wake) n=135 ##### Variables * : * value: microdialysate cortisol concentration, in nmol/L * Minutes: time in minutes, relative to wake time * bins: * SID: unique anonymous participant identified #### File: healthy\_cohort\_misaligned\_wake\_Cortisol\_LME\_R\_n\_64.csv **Description:**  ##### Variables * : * value: microdialysate cortisol concentration, in nmol/L * Minutes: time in minutes, relative to wake time * bins: * SID: unique anonymous participant identified #### File: healthy\_cohort\_shortest\_quartile\_Cortisol\_LME\_R\_n\_51.csv **Description:**  ##### Variables * : * value: microdialysate cortisol concentration, in nmol/L * Minutes:  time in minutes, relative to wake time * bins: * SID: microdialysate cortisol concentration, in nmol/L ## Code/software Included is the R script used to run the mixed linear models described in the paper. Within the code the version number of R and associated packages is included and reproduced below platform       x86_64-w64-mingw32               arch           x86_64                           os             mingw32                           crt            ucrt                             system         x86_64, mingw32                   status                                           major          4                                 minor          3.1                               year           2023                             month          06                               day            16                               svn rev        84548                             language       R                                 version.string R version 4.3.1 (2023-06-16 ucrt) nickname       Beagle Scouts report_0.5.7  nlme_3.1-162  lspline_1.0-0 ## Access information Other publicly accessible locations of the data: * Data was derived from the following sources: * UiB Open Research Data https://doi.org/10.18710/5TW8YF.