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      Is Cortisol Excretion Independent of Menstrual Cycle Day? A Longitudinal Evaluation of First Morning Urinary Specimens

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          Abstract

          Background

          Cortisol is frequently used as a marker of physiologic stress levels. Using cortisol for that purpose, however, requires a thorough understanding of its normal longitudinal variability. The current understanding of longitudinal variability of basal cortisol secretion in women is very limited. It is often assumed, for example, that basal cortisol profiles do not vary across the menstrual cycle. This is a critical assumption: if cortisol were to follow a time dependent pattern during the menstrual cycle, then ignoring this cyclic variation could lead to erroneous imputation of physiologic stress. Yet, the assumption that basal cortisol levels are stable across the menstrual cycle rests on partial and contradictory evidence. Here we conduct a thorough test of that assumption using data collected for up to a year from 25 women living in rural Guatemala.

          Methodology

          We apply a linear mixed model to describe longitudinal first morning urinary cortisol profiles, accounting for differences in both mean and standard deviation of cortisol among women. To that aim we evaluate the fit of two alternative models. The first model assumes that cortisol does not vary with menstrual cycle day. The second assumes that cortisol mean varies across the menstrual cycle. Menstrual cycles are aligned on ovulation day (day 0). Follicular days are assigned negative numbers and luteal days positive numbers. When we compared Models 1 and 2 restricting our analysis to days between −14 (follicular) and day 14 (luteal) then day of the menstrual cycle did not emerge as a predictor of urinary cortisol levels (p-value >0.05). Yet, when we extended our analyses beyond that central 28-day-period then day of the menstrual cycle become a statistically significant predictor of cortisol levels.

          Significance

          The observed trend suggests that studies including cycling women should account for day dependent variation in cortisol in cycles with long follicular and luteal phases.

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          Most cited references56

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          How stress influences the immune response.

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            Why do we respond so differently? Reviewing determinants of human salivary cortisol responses to challenge.

            Stress and stress-related health impairments are major problems in human life and elucidating the biological pathways linking stress and disease is of substantial importance. However, the identification of mechanisms underlying a dysregulation of major components of the stress response system is, particularly in humans, a very challenging task. Salivary cortisol responses to diverse acute challenge paradigms show large intra- and interindividual variability. In order to uncover mechanisms mediating stress-related disorders and to potentially develop new therapeutic strategies, an extensive phenotyping of HPA axis stress responses is essential. Such a research agenda depends on substantial knowledge of moderating and intervening variables that affect cortisol responses to different stressors and stimuli. The aim of this report is, therefore, to provide a comprehensive summary of important determinants of, in particular, human salivary cortisol responses to different kinds of laboratory stimuli including acute psychosocial stress as well as pharmacological provocation procedures. This overview demonstrates the role of age and gender, endogenous and exogenous sex steroid levels, pregnancy, lactation and breast-feeding, smoking, coffee and alcohol consumption as well as dietary energy supply in salivary cortisol responses to acute stress. Furthermore, it briefly summarizes current knowledge of the role of genetic factors and methodological issues in terms of habituation to repeated psychosocial stress exposures and time of testing as well as psychological factors, that have been shown to be associated with salivary cortisol responses like early life experiences, social factors, psychological interventions, personality as well as acute subjective-psychological stress responses and finally states of chronic stress and psychopathology.
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              Free cortisol levels after awakening: a reliable biological marker for the assessment of adrenocortical activity.

              In three independent studies, free cortisol levels after morning awakening were repeatedly measured in children, adults and elderly subjects (total n=152). Cortisol was assessed by sampling saliva at 10 or 15 minute intervals for 30-60 minutes, beginning at the time of awakening for two days (Study 1 and 2) or one (Study 3) day, respectively. In all three studies, free cortisol levels increased by 50-75% within the first 30 minutes after awakening in both sexes on all days. Premenopausal women consistently showed a stronger increase with a delayed peak after awakening compared to men on all days. In Study 2, there was a tendency for lower early morning free cortisol levels for women taking oral contraceptives (p=.10). Stability of the area under the curve (AUC) of the early morning free cortisol levels over the three (Study 1 and 2) or two (Study 3) days ranged between r=.39 and r=.67 (p<.001). Neither age, weight, nor smoking showed an effect on baseline or peak cortisol levels. Sleep duration, time of awakening and alcohol consumption also appeared to be unrelated to early morning free cortisol levels. From these data we conclude that in contrast to single assessments at fixed times, early morning cortisol levels can be a reliable biological marker for the individual's adrenocortical activity when measured repeatedly with strict reference to the time of awakening.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                31 March 2011
                : 6
                : 3
                : e18242
                Affiliations
                [1 ]Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
                [2 ]Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada
                [3 ]School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
                [4 ]Department of Pathology, University of Michigan, Ann Arbor, Michigan, United States of America
                University of Illinois at Champaign-Urbana, United States of America
                Author notes

                Analyzed the data: RMA CC PAN. Contributed reagents/materials/analysis tools: BGE DSM. Wrote the paper: PAN RMA RW CC BGE. Conceived and designed the study: PAN DSM BGE. Performed the study: PAN. Data collection: PAN.

                Article
                PONE-D-10-03778
                10.1371/journal.pone.0018242
                3069066
                21483825
                76ea9d6a-bec9-4a89-bd29-3aa085270a6a
                Nepomnaschy et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 14 October 2010
                : 1 March 2011
                Page count
                Pages: 7
                Categories
                Research Article
                Biology
                Anatomy and Physiology
                Endocrine System
                Endocrine Physiology
                Hormones
                Physiological Processes
                Chronobiology
                Reproductive System
                Reproductive Physiology
                Medicine
                Diagnostic Medicine
                Pathology
                General Pathology
                Biomarkers
                Epidemiology
                Biomarker Epidemiology
                Women's Health
                Social and Behavioral Sciences
                Anthropology
                Anthropometry
                Biological Anthropology
                Physical Anthropology
                Psychology
                Psychological Stress

                Uncategorized
                Uncategorized

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