Exploring the cortisol awakening response in premenstrual dysphoric disorder and in healthy females across the menstrual cycle PDF Free Download
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Original Article
Exploring the cortisol awakening response in
premenstrual dysphoric disorder and in healthy
females across the menstrual cycle
Kim Hoffmann, Rachel G. Zsido, Arno Villringer, Swen Hesse, Osama Sabri*, Veronika Engert*and
Julia Sacher*
Background
Research suggests there are alterations in the cortisol
awakening response (CAR) in patients with premenstrual
dysphoric disorder (PMDD), as demonstrated by delayed
cortisol peaks and flatter diurnal cortisol slopes compared to
healthy controls. While inconsistent, previous work also
demonstrates a relation between alterations in CAR, prefrontal
serotonin transporter (5-HTT) binding and severity of depres-
sive symptoms.
Aims
This longitudinal study explores CAR in relation to midbrain
and prefrontal 5-HTT binding and depressive symptoms in
patients with PMDD and in healthy controls across the
menstrual cycle.
Method
Thirty patients with PMDD and 29 controls each provided 3
saliva samples for assessment of CAR (awakening, +30 min,
+60 min) and 5 to assess the diurnal cortisol slope (09.00,
12.00, 15.00, 18.00, 21.00 h) during the periovulatory and
premenstrual phases. [11C]DASB positron emission tomogra-
phy scans were performed to measure 5-HTT non-displaceable
binding potential (BP
ND
). Depressive symptoms were assessed
using the Hamilton Depression Rating Scale. Associations
between cortisol measures, 5-HTT BP
ND
and depressive
symptoms were examined using linear mixed-effects models,
independent t-tests, mixed analysis of variance (ANOVA) and
Spearman rank correlations.
Results
A significant interaction effect between group and cycle phase
was found for cortisol peak concentrations (estimate =0.78,
p=0.05, d=0.62, 95% CI: [0.01, 1.56]; and corrected for
awakening cortisol concentration: estimate =0.90, p=0.02,
d=0.77, 95% CI: [0.15, 1.66]). Cortisol peak concentrations
correlated negatively with both midbrain 5-HTT BP
ND
(r=−0.34,
p<0.01, R2=0.12) and depressive symptoms (r=−0.30,
p=0.02, R2=0.09) during the premenstrual phase.
Conclusions
Patients with PMDD showed attenuated cortisol peaks in the
periovulatory phase compared with healthy controls, who
demonstrated plastic changes across the cycle. Results point
towards an interplay between the stress and the serotonergic
system, as well as to the severity of depressive symptoms during
the premenstrual phase.
Keywords
Cortisol awakening response; premenstrual dysphoric disorder;
menstrual cycle; 5-HTT BP
ND
; depressive symptoms.
Copyright and usage
© The Author(s), 2025. Published by Cambridge University Press
on behalf of Royal College of Psychiatrists. This is an Open
Access article, distributed under the terms of the Creative
Commons Attribution licence (https://creativecommons.org/
licenses/by/4.0/), which permits unrestricted re-use, distribution
and reproduction, provided the original article is properly cited.
Premenstrual dysphoric disorder (PMDD) is a severe affective
disorder, characterised by cyclic affective and physical symptoms that
emerge during the luteal phase of the menstrual cycle and remit
following menstruation.1While the exact pathophysiology remains
unclear, accumulating evidence suggests dysregulation of the
hypothalamic–pituitary–adrenal (HPA) axis2and altered serotoner-
gic functioning3as the key mechanisms underlying PMDD. Given
that the HPA axis plays a crucial role in coordinating stress
responses4and interacts closely with the serotonergic system,5
disruptions in these systems may contribute to the heightened
affective and physiological sensitivity observed in PMDD.6
One widely studied marker of HPA axis activity is the cortisol
awakening response (CAR), a rapid rise in cortisol levels occurring
within the first 30–45 min after waking.7CAR is influenced by both
endogenous and exogenous factors, including stress,8vulnerability
to affective disorders9and neuroendocrine regulation.10 While
females display an increased CAR compared with males,11 no CAR
differences have yet been reported between the follicular and luteal
phases in healthy, naturally cycling females, except for a blunted
CAR during menses12 and an increased CAR during ovulation.13
However, in the only study directly comparing patients with
PMDD and healthy controls, a delayed CAR peak and flattened
diurnal cortisol slope were observed in patients with PMDD,14
suggesting dysregulated HPA axis activity in this population.
One possible mechanism underlying this dysregulation is
serotonergic dysfunction, which has long been implicated in
PMDD.15 Given that selective serotonin reuptake inhibitors exert
their therapeutic effects by binding to the serotonin transporter
(5-HTT), and pose an effective pharmacological treatment for
PMDD,16 alterations in 5-HTT expression or function may
contribute to the abnormal CAR observed in PMDD. However,
no study has yet examined the interaction between CAR and
5-HTT in PMDD. This represents a critical gap in understanding
how stress regulation and serotonin function interact in this disorder.
The present study explores the interactions among CAR,
5-HTT binding levels and depressive symptoms. Specifically, we
aim to explore whether patients with PMDD exhibit a dysregulated
CAR, differing from controls depending on the menstrual cycle
phase. Due to the role of oestradiol in stress17 and emotion
regulation,18 the periovulatory phase, characterised by an oestradiol
peak, is contrasted with the premenstrual phase, characterised by
declining oestradiol levels and PMDD symptoms. We further
explore the association between 5-HTT binding levels and CAR,
given that altered serotonergic function could contribute to HPA
*Joint senior authors.
The British Journal of Psychiatry (2025)
1–9. doi: 10.1192/bjp.2025.10432
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https://doi.org/10.1192/bjp.2025.10432 Published online by Cambridge University Press
axis dysregulation in PMDD. Finally, we explore the relationship
between CAR and affective symptoms that may vary across the
cycle, possibly reflecting heightened sensitivity to hormonal
fluctuations in PMDD.
By integrating HPA axis function, serotonergic regulation and
menstrual cycle-dependent mood changes, this study provides a
novel perspective on the neurobiological underpinnings of PMDD.
Understanding these mechanisms may inform individualised
treatment strategies, particularly regarding the serotonergic
modulation of stress responses in PMDD.
Method
Participants
For this longitudinal study, participants were either healthy
(n=29) or diagnosed with PMDD (n=30). Participants were
all female, between 19 and 34 years of age and reported having
regular menstrual cycles (length of 23–35 days in the past 6
months). Participants had not used hormonal contraceptives within
1 year of study participation, were not pregnant, postpartum
(within 1 year after delivery) or (peri)menopausal and had not
recently undergone abortion (within 1 year). Eligible participants
were non-smokers in good physical health with no lifetime history
of, or comorbid, Axis I or Axis II disorder19,20 (for controls and
patients with PMDD, respectively); no current or lifetime
antidepressant use; no use of prescription medications or herbal
supplements within the past 2 months; and no use of over-the-
counter medications within the past 2 weeks. For the PMDD group,
the same inclusion criteria applied, but participants additionally
reported a history of premenstrual symptoms (within the past 6
months). PMDD diagnosis was based on the Structured Clinical
Interview for DSM-5 (SCID-5)19 performed by a licensed
psychiatrist (J.S.), and participants further met the PMDD criteria
of the Premenstrual Symptoms Screening Tool (PSST).21 The final
group allocation was assessed by agreement between two
independent researchers.
For the parent study,3which assessed 5-HTT binding across the
menstrual cycle in PMDD and health, an a priori power analysis
performed with G*Power 2019 for Windows (Heinrich Heine
Universität Düsseldorf, Düsseldorf, Germany; see https://www.
psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-
arbeitspsychologie/gpower) yielded a required sample of N=52 to
detect a moderate effect size (0.4), at a power of 0.8 and an α-level of
0.05 (https://osf.io/fvghx). The current exploratory study was pre-
registered as an amendment of this parent study (https://osf.io/
ygfzs). Written informed consent was obtained from all partic-
ipants. The authors assert that all procedures contributing to this
work comply with the ethical standards of the relevant national and
institutional committees on human experimentation, and with the
Helsinki Declaration of 1975 as revised in 2013. All procedures
involving human participants were approved by the Ethics
Committee of the Faculty of Medicine, University of Leipzig
(approval no. 077-11-ff).
Procedure
Participants underwent two assessments: the first within 24 h of
their estimated ovulation (periovulatory phase), the second 13–14
days after ovulation/within 3 days of onset of the next menses
(premenstrual phase). The order of testing sessions was randomised
between participants. Testing sessions included fasting blood
samples for endocrine assessment, a series of questionnaires, a
neuropsychological test battery and [11C]DASB positron emission
tomography (PET) and magnetic resonance imaging (MRI) scans,
matched for season and time of day (Fig. 1(a)). Participants were
instructed to self-collect saliva samples in the morning of, and
across, each testing day (Fig. 1(b)).
Menstrual cycle monitoring
For accurate determination of the two cycle phases, participants
were asked to track their basal body temperature, possible bleeding
and disruptive factors for at least one menstrual cycle before study
participation, using a smartphone app (myNFP Web Classic v2.0.0.,
myNFP GmbH, Tübingen, Germany; see https://www.mynfp.de/).
Folliculometries were performed by a gynaecologist to determine
the precise time of ovulation. Participants used urine ovulation tests
(Diagnostik Nord GmbH hLK-K20 hLH Kassettentest) to detect
the luteinising hormone surge preceding ovulation. Additionally,
fasting blood serum samples were collected using S-Monovettes®
(Sarstedt, Germany) to measure ovarian hormones at each testing
session. Oestradiol and progesterone concentrations were deter-
mined using liquid chromatography–tandem mass spectrometry
(LC–MS/MS). Follicle-stimulating hormone (FSH) and luteinising
hormone concentrations were determined using electrochemilu-
minescence immunoassay (ECLIA, Roche).
Cortisol sampling
On each day of testing, participants self-collected cortisol saliva
samples with Salivettes®(Sarstedt, Germany) at home immediately
following awakening, as well as 30 and 60 min post-awakening.
Participants were instructed not to brush their teeth or eat or drink
anything other than water within 10 min prior to saliva sampling.
Additional saliva samples were provided at 09.00 and 12.00.
Participants were instructed to store saliva samples in the
refrigerator until their delivery to the laboratory, where they were
then stored at −80°C. Cortisol saliva samples were analysed using a
time-resolved fluorescence immunoassay22 at the biochemical
laboratory of the University of Trier, with intra- and inter-assay
coefficients of variation of 4.0−6.7 and 7.1−9.0%, respectively.
To quantify CAR, multiple indices have been proposed.23
Informed by CAR research showing delayed cortisol peaks in
patients with PMDD,14 here we determined the cortisol peak
(maximal cortisol concentration) within the second and third saliva
samples (30 and 60 min post-awakening) per cycle phase. Other
pre-registered outcomes (i.e. area under the curve with respect to
increase, delta) have been included as supplementary analyses
(Supplementary Tables 1and 2available at https://doi.org/10.1192/
bjp.2025.10432).
Mood assessment
In all participants, the severity of depressive symptoms experienced
within the past week was assessed with the Hamilton Depression
Rating Scale (HAM-D, 17 items).24 Perceived stress within the
past 4 weeks was derived from the Perceived Stress Scale (PSS,
10 items).25
Neuroimaging
We applied the radiotracer [11C]-3-amino-4-(2-dimethylamino-
methyl-phenylsulfanyl)-benzonitrile ([11C]DASB)26 to assess sero-
tonin transporter binding using PET in vivo. Primary outcomes
were midbrain3and prefrontal27 5-HTT non-displaceable binding
potentials (BP
ND
), using the cerebellum as reference region.
Data preparation
Hormone values below the detection threshold were replaced by
their respective minimum value. According to expert guidelines,28
Hoffmann et al
2
https://doi.org/10.1192/bjp.2025.10432 Published online by Cambridge University Press
raw cortisol concentrations were square-root transformed to
account for positively skewed distribution,29 and outliers exceeding
mean ±three times the standard deviation were winsorised to the
respective maximum or minimum values,30 before determining
cortisol peaks.
Statistical analysis
One linear mixed-effects model was built on cortisol peak,
including group (control, PMDD), phase (periovulatory, premen-
strual), the interaction between group and phase, and depressive
symptoms (HAM-D scores) as fixed effects. A random intercept per
participant accounted for inter-individual differences. To control
for baseline cortisol concentrations, we added awakening cortisol
concentration as a fixed effect, changing the cortisol peak into a
proxy for cortisol increase. Similarly, the influence of covariates
(oestradiol, progesterone, age, body mass index, PSS scores, time of
awakening, hours of sleep, sleep quality) was checked.
Exploratively, cortisol concentrations at each time point
(S1–8) and changes in CAR cortisol concentrations (awakening
to +30 min, +30 min to +60 min) were assessed using multiple
linear mixed-effects models, with the model equation on cortisol
Luteal phaseFollicular phase
(a)
(b)
Study design
Month
E2
P4
1 14 28 days
Periovulatory
Premenstrual
Cortisol concentration
Awakening
S1
S8
S7
S6
S5
S4
S3
S2
+30 min
cortisol peak
+60 min 09.00 h 12.00 h 15.00 h 18.00 h 21.00 h Time
Day
8x
Saliva sampling
Fig. 1 (a) Study design. All participants were tested during the periovulatory and the premenstrual phase. Menstrual cycle phases were
determined using cycle tracking, folliculometries and urine-based ovulation tests. Additionally, blood samples were drawn at each testing
day to verify cycle phases by ovarian hormone levels. Participants performed positron emission tomography (PET) and magnetic resonance
imaging (MRI) scans, undertook a neurocognitive test battery, filled in a series of questionnaires and collected saliva samples at each
testing day. (b) Saliva sampling. Participants self-collected eight saliva samples (S1–8) across each testing day. The cortisol peak refers to
the maximum cortisol concentration within the second and third saliva sample. E2, estradiol; P4, progesterone.
Exploring the cortisol awakening response in premenstrual dysphoric disorder
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peak accounting for awakening cortisol. In addition to the pre-
registered analyses, the relationships between cortisol peak and
midbrain and prefrontal 5-HTT BP
ND
, as well as HAM-D scores,
were assessed using a series of Spearman rank correlations.
Lastly, demographics, questionnaire data and ovarian hormone
concentrations were compared between groups and phases using
independent t-tests and mixed analysis of variance (ANOVA).
Statistical analyses were performed with R version 4.5.0 for
Linux (R Core Team, Vienna, Austria; see https://www.R-project.
org). Statistical significance was assessed at a critical p-value of 0.05
and, in the case of linear mixed-effects model estimates, verified
using model comparisons by means of chi-square (X2)tests and
Bayes factors approximated by Bayesian information criterion
(BIC), comparing models including and excluding the estimate of
interest, if possible. If a significant interaction was observed, post
hoc tests were performed to explore simple effects. Bonferroni
correction was applied to account for multiple comparisons, if
necessary. D(fixed-effect estimate/square root of the sum of
variances of random effects) served as an effect size for linear
mixed-effects model estimates, and R2for Spearman rank
correlations.
Results
Sample characteristics and demographics
Sample characteristics and demographics are displayed in Table 1.
Patients with PMDD were significantly older than controls, with no
group differences in body mass index. Premenstrual PSST scores
were significantly higher in patients with PMDD compared with
healthy controls. Oestradiol levels were significantly higher in the
periovulatory phase compared with the premenstrual (F=33.39,
p<0.001), while progesterone levels significantly increased across
phases (F=30.68, p<0.001), with no difference in absolute
ovarian hormone levels between groups. Patients with PMDD
showed overall higher depressive symptoms (HAM-D scores) than
controls, and an increase from the periovulatory phase to the
premenstrual. Participants reported higher perceived stress (PSS
scores) in the premenstrual phase compared with the periovulatory
(F=11.14, p<0.01), with no difference between patients with
PMDD and controls. No group or cycle phase differences were
found in awakening cortisol concentrations.
Missing data
Two participants sampled salivary cortisol during only one
menstrual cycle phase. Additionally, three cortisol samples were
missing at awakening, two at 60 min post-awakening and 12 at later
sampling time points. Missing cortisol values were addressed using
suitable linear mixed-effects models. One oestradiol and three
progesterone concentrations below the detection threshold were
replaced by the respective minimal detection values. PSS scores
were missing for 10 participants (n=4 PMDD), while reports of
hours and quality of sleep were incomplete for 21 participants
(n=10 PMDD). For 6 awakening cortisol samples (n=3 PMDD),
the time of awakening was unknown.
Cortisol peak
We found a marginally significant interaction between group and
phase on cortisol peak (estimate =0.78, t=1.96, p=0.05, d=0.62;
Fig. 2(a)). One model including the interaction improved its fit
(X2=3.92, p=0.05), but a Bayes factor of 0.66 showed anecdotal
evidence in favour of the model, excluding the interaction.
Disentangling simple effects showed that the interaction was driven
by lower cortisol peaks in patients with PMDD compared with
controls, specifically during the periovulatory phase.
Correcting for awakening cortisol concentrations strengthened
the interaction (estimate =0.90, t=2.30, p=0.02, d=0.77), with a
Bayes factor of 8.39 ×103, supporting this more complex model.
Additionally, and as expected, a significant positive main effect of
awakening cortisol on cortisol peak concentration was found
(estimate =0.55, t=4.10, p<0.01, d=0.47). When excluding
observations from this complex model for which participants
reported a delay of ≥10 min in saliva sampling, the interaction was
further strengthened (estimate =0.99, t=2.23, p=0.03, d=0.84).
Correcting for self-reported perceived stress levels, time of awakening
and self-reported hours and quality of sleep strengthened the
interaction further (see Supplementary Table 3for missing data). The
addition of body mass index, age and oestradiol and progesterone
concentrations as covariates did not improve the model’sfit.
In sum, patients with PMDD showed attenuated cortisol peaks
compared with controls during the periovulatory phase.
Controlling for awakening cortisol concentration strengthened
this interaction. However, the interaction did not survive correction
for testing of three CAR indices.
Table 1 Sample characteristics and demographics
Variable Group Mean (s.d.) d.f. tp
Age CTL 24.3 (3.0) 57 3.31 <0.01a
PMDD 27.5 (4.4)
BMI CTL 22.87 (3.07) 57 -2.11 0.12a
PMDD 21.42 (2.14)
PSST CTL 8.31 (7.69) 57 12.86 <0.001a
PMDD 34.37 (7.88)
Periovulatory Premenstrual d.f. Fp
E2 CTL 663.00 (441.42) 326.94 (226.94) 57 0.05 0.83
PMDD 762.50 (548.78) 400.87 (220.71)
P4 CTL 3.56 (4.39) 14.14 (12.59) 57 0.14 0.71
PMDD 5.57 (5.59) 17.70 (14.19)
HAM-D CTL 1.72 (2.23) 2.76 (2.85) 57 81.28 <0.001
PMDD 3.73 (3.20) 10.53 (3.26)
PSS CTL 12.00 (6.12) 13.91 (7.20) 47 0.02 0.90
PMDD 15.31 (6.17) 17.42 (6.77)
Awakening cortisol CTL 5.92 (3.35) 6.91 (4.41) 52 1.48 0.23
PMDD 6.03 (4.81) 5.21 (3.79)
Sample characteristics and demographic variables between groups and menstrual cycle phases provided as mean (standard deviation). Statistics refer to group differences or group and
cycle phase interactions. BMI, body mass index; CTL, control; E2, oestradiol; HAM-D, Hamilton Depression Rating Scale; P4, progesterone; PMDD, premenstrual dysphoric disorder; PSS,
Perceived Stress Scale; PSST, Premenstrual Symptom Screening Tool.
a. Bonferroni adjusted p-value controlling for three group comparisons.
Hoffmann et al
4
https://doi.org/10.1192/bjp.2025.10432 Published online by Cambridge University Press
Cortisol concentration across time
Groups did not differ in regard to their cortisol concentrations at
awakening, or at 30 min post-awakening, with similar concen-
trations across cycle phases. Mirroring the effect found for cortisol
peaks, a significant interaction between group and phase was
detected at 60 min post-awakening (estimate =1.14, t=2.58,
p=0.01, d=0.87), not surviving correction for comparison of
eight cortisol sampling time points. Disentangling simple effects
revealed significantly lower cortisol concentrations at 60 min post-
awakening in patients with PMDD compared with controls during
the periovulatory phase. No group or cycle phase differences were
found for later cortisol sampling points (Fig. 2(b)).
Focusing on cortisol change, both groups showed similar
increases in cortisol from awakening to 30 min post-awakening
across cycle phases. For cortisol change from 30 to 60 min post-
awakening, we found a marginally significant interaction between
group and phase (estimate =0.77, t=1.97, p=0.05, d=0.79), not
surviving correction for testing of two cortisol changes.
Disentangling simple effects revealed higher cortisol increases
from 30 to 60 min post-awakening during the periovulatory phase
compared with the premenstrual in controls, while patients with
PMDD showed similar cortisol increases across cycle phases (Fig. 2(b)).
In sum, explorative analyses propose lower cortisol concen-
trations at 60 min post-awakening in patients with PMDD
compared with controls during the periovulatory phase. Healthy
controls displayed a tendency for higher cortisol increases from 30
to 60 min during the periovulatory phase compared with the
premenstrual.
Cortisol peak and 5-HTT BP
ND
Cortisol peaks correlated significantly with midbrain 5-HTT BP
ND
(r=−0.20, p=0.03, R2=0.04). Splitting by cycle phase revealed
that this association was present only in the premenstrual phase
(r=−0.34, p<0.01, R2=0.12) and not in the periovulatory phase
(r=−0.04, p=0.78). In detail, increasing cortisol peaks were linked
to decreasing midbrain 5-HTT BP
ND
in the premenstrual cycle phase
(Fig. 3(a)), surviving correction for testing binding potentials in two
brain regions across two cycle phases, but not for testing three CAR
Cortisol peak (nmoI/L)
5-HTT BPND midbrain
Phase
HAM-D scores
Cortisol peak (nmoI/L)
50
40
30
20
10
0
50
40
30
20
10
0
0 5 10 15
123
**
Periovulatory
Premenstrual
(a) (b)
Cortisol peak vs 5-HTT BPND midbrain Cortisol peak vs depressive symptoms
Fig. 3 Cortisol peak concentrations (nmol/L) against (a) midbrain 5-HTT BP
ND
per cycle phase, and (b) HAM-D scores per cycle phase. Raw
cortisol peak concentrations are plotted to facilitate visualisation. Asterisks indicate significance levels of p<0.05. Differently shaded dots
represent individual data points. Differently shaded lines indicate a significant correlation, with shaded grey areas representing a 95%
confidence interval. HAM-D, Hamilton Depression Rating Scale; 5-HTT BP
ND
, non-displaceable serotonin transporter binding potentials.
Cortisol peak
Cycle phase
Cortisol peak (nmol/L)
50
40
30
20
10
0
Periovulatory Premenstrual
Diurnal cortisol slope
Time
Cortisol (nmol/L)
15
10
5
00 min 30 min 60 min 09.00 h 12.00 h 15.00 h 18.00 h 21.00 h
Group CTL periovulatory CTL premenstrual
PMDD periovulatory PMDD premenstrual
(a)
(b)
*
*
*
I
Fig. 2 (a) Cortisol peak concentrations (nmol/L) during the menstrual
cycle (periovulatory vs premenstrual) in both groups (patients with
premenstrual dysphoric disorder (PMDD) vs healthy controls). Raw
cortisol peak concentrations are plotted to facilitate visualisation.
Thin horizontal lines indicate median concentrations and crosses
indicate mean concentrations per group and phase. Dots represent
individuals’peak cortisol concentrations. Asterisks represent
significant levels of p≤0.05. (b) Diurnal cortisol slopes per group
and cycle phase. Raw mean cortisol concentrations per time point
are plotted to facilitate visualisation. Asterisks represent significant
levels of p≤0.05. CTL, control.
Exploring the cortisol awakening response in premenstrual dysphoric disorder
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https://doi.org/10.1192/bjp.2025.10432 Published online by Cambridge University Press
indices. No association was found between cortisol peaks and
prefrontal 5-HTT BP
ND
. No associations between 5-HTT binding
and other CAR indices were found.
Cortisol peak and depressive symptoms
Cortisol peaks correlated significantly with HAM-D scores
(r=−0.26, p<0.01, R2=0.07). Splitting by cycle phase revealed
that this association was present only in the premenstrual phase
(r=−0.30, p=0.02, R2=0.09) and not in the periovulatory phase
(r=−0.21, p=0.11). In detail, decreasing cortisol peaks were
linked to increasing depressive symptoms in the premenstrual
phase (Fig. 3(b)), surviving correction for testing this correlation in
two cycle phases, but not for testing three CAR indices. No
associations between depressive symptoms and other CAR indices
were found.
Discussion
Patients with PMDD exhibited attenuated cortisol peaks during the
periovulatory phase compared with healthy controls. Additionally,
cortisol peaks were negatively associated with midbrain serotonin
transporter binding and depressive symptoms during the premen-
strual phase. Study findings suggest an altered stress system
regulation in PMDD, and highlight the need for critical reflection
on CAR guidelines when studying the menstrual cycle and related
mood disorders.
Comparison with previous studies
Our cortisol peak finding in PMDD is partially consistent with
previous work14 showing delayed cortisol peaks in patients with
PMDD compared with controls across the menstrual cycle. Studies
on premenstrual syndrome (PMS), a condition of psychological
and somatic symptoms before menses onset below clinical-level
thresholds in severity, also report a flat CAR during menses and
attenuated CAR at 45 and 60 min post-awakening during the mid-
follicular and premenstrual phases.12,31 Given the limited research
on CAR in PMDD across the menstrual cycle, larger longitudinal
studies employing dense-sampling methods and assessments of
individualised, multidimensional stress responses are warranted to
develop a systematic understanding of CAR signature patterns
in PMDD.
Our cortisol peak finding in controls partially aligns with a
previous study13 reporting a significantly higher increase in cortisol
from awakening to peak levels during ovulation, compared with
menses and the follicular and luteal phases. However, most studies
do not report differences in CAR across the menstrual cycle.32–34
Discrepancies may arise due to study designs that did not confirm
ovulation through objective tests32 or oestradiol peaks,33 or that
omitted the periovulatory phase.34 In contrast, our study included
the periovulatory phase, validated through folliculometries,
luteinising hormone ovulation tests, serum ovarian hormone levels
and digital menstrual cycle tracking, ensuring accurate cycle phase
determination.
Research highlights robust gender differences in the HPA axis
response to external stressors, including psychosocial stress,34 as
well as variations in basal HPA axis activity35 and reactivity,36
across the menstrual cycle. However, the mechanism underlying
the interaction of ovarian hormone fluctuations and HPA axis
response remains unclear. The CAR also exhibits gender differ-
ences11 and menstrual cycle effects, although for the latter the
current evidence is mixed. While some studies link CAR indices to
oestradiol and progesterone,12,32 we found no such association
between cortisol peak and ovarian hormone concentrations.
Moreover, group differences in cortisol peaks in this study cannot
be attributed to differences in absolute oestradiol or progesterone
levels, aligning with previous work showing no absolute difference,
but rather an altered sensitivity to normal hormonal fluctuations, in
patients with PMDD.37
In the current study, both controls and patients with PMDD
exhibited relatively delayed cortisol peak concentrations. From all
cortisol peaks (n=116), 20.69% occurred at 30 min and 29.31% at
60 min post-awakening in patients with PMDD, compared with
23.28 and 26.72%, respectively, in controls, suggesting a tendency
for delayed cortisol peaks in PMDD. Furthermore, excluding 11
observations for which participants reported a delay of ≥10 min in
CAR saliva sampling strengthened the interaction effect. Non-
responses in CAR (≤2.5 nmol/L cortisol increase) occurred in
24.56% of observations, consistent with other studies,38 indicating
that non-compliance and non-responses cannot explain the
observed delayed cortisol peaks.
The prominence of delayed peaks in this study may have
resulted from the absence of systematic assessment of cortisol peak
timing across the menstrual cycle. Previous research has shown that
females tend to peak later than males, at around 45 min.11,38
Patients with PMDD have shown delayed cortisol peaks at 45
compared to 30 min in controls.14 Only a few studies have observed
peaks as late as 60 min post-awakening across the menstrual cycle,32
and specifically for the follicular and luteal phases.39 Our findings
support the notion of delayed cortisol peaks at 60 min post-
awakening in patients with PMDD across the menstrual cycle, as
well as in naturally cycling females during ovulation. This study
highlights the need for critical reflection on, and extending the time
window of, saliva sampling time points for CAR research across the
menstrual cycle. The CAR in patients with PMDD and healthy
females remains under-explored.
Altered stress markers, particularly a flattened diurnal cortisol
slope, have been linked to poorer health outcomes.40 Similarly,
alterations in CAR have been reported for various disorders. For
example, while patients with post-traumatic stress disorder exhibit
an attenuated CAR,41 the direction of findings varies for clinical
depression.42 To reconcile these mixed results, it has been suggested
that CAR flexibility, rather than magnitude, may be a more
meaningful measure.43 For example, participants with high self-
reported well-being showed greater variability in CAR indices in
line with external demands (i.e. weekends versus weekdays), while
this variability was less in participants with low self-reported well-
being.43 Applying this to our findings suggests that patients with
PMDD, and with more severe depressive symptoms, may lack the
flexibility to adapt their cortisol peak across the menstrual cycle, a
capacity that healthy females seem to possess. The menstrual cycle,
representing a monthly reoccurring phenomenon affecting most
females during their reproductive years, imposes physiological
demands that potentially require a flexible upregulation of CAR.
The concept of CAR flexibility warrants further investigation,44
especially across the menstrual cycle, and may have significant
clinical relevance for menstrual cycle-related disorders such
as PMDD.
Reimold et al45 were the first to report an inverse relationship
between thalamic 5-HTT binding and increased cortisol response
to a combined dexamethasone–corticotrophin test, interpreted as
being driven by lower thalamic 5-HTT availabilities in their clinical
sample (unmedicated patients with obsessive–compulsive disorder
and major depressive disorder) compared with controls. Pioneering
work by Frokjaer et al27,46 on the relationship between CAR and the
serotonergic system initially showed a positive association between
the area under the curve and prefrontal 5-HTT BP
ND
in healthy
participants (N=32, 7 females, 19.7–81.7 years),27 and in abstinent
3,4-Methylenedioxymethamphetamine (MDMA) users (N=18
Hoffmann et al
6
https://doi.org/10.1192/bjp.2025.10432 Published online by Cambridge University Press
users, 2 females, 20.1–33.6 years).46 In a larger follow-up study, this
finding could not be replicated (N=90, 67 females, 18.4–47.7
years).47 No study has yet longitudinally investigated the relation-
ship between CAR indices and 5-HTT availability across the
menstrual cycle in both healthy females and patients with PMDD.
In the current study, cortisol peaks were negatively correlated
with midbrain 5-HTT BP
ND
during the premenstrual phase,
suggesting a facilitatory mechanism between the midbrain
serotonergic and stress systems towards the end of the menstrual
cycle. We also tested this relationship for the prefrontal cortex given
the findings by Frokjaer et al,27 who emphasised this area as their
main region of interest due to the expression of glucocorticoid and
mineralocorticoid receptors. The availability of 5-HTT, however, is
low in prefrontal cortical areas,48 which may partly explain why
their results did not replicate in a larger sample.47 The studied
samples also differed in demographics, because one contained
mostly men of a wider age range27 while the other contained
primarily young women.47 Since we observed no association
between prefrontal 5-HTT BP
ND
with cortisol peaks, our results
align with the more recent findings.47 Understanding and
characterising the relationship between the serotonergic and stress
systems in health, but also in stress-related mood disorders, is of
great relevance.
Underlying biological mechanisms
The mechanisms linking cortisol dysregulation and depressive
symptoms in PMDD may involve a complex interplay between the
serotonergic system and HPA axis functioning. Our results,
showing a negative correlation between cortisol peaks and
depressive symptoms in all participants during the premenstrual
phase, align with previous findings linking different CAR indices to
mood regulation.31,32 Increased 5-HTT binding potential during the
premenstrual phase, previously demonstrated in this PMDD
sample,3may reflect a compensatory mechanism stabilising cortisol
responses to stress. Genetic factors, such as serotonin transporter
genotype,49 and epigenetic factors, such as methylation of the
serotonin transporter gene,50 have also been linked to cortisol
responses, indicating that serotonergic regulation at the gene level
may contribute to HPA axis dysfunction.
Strengths and limitations
The present study is the first to systematically investigate CAR
across the menstrual cycle in healthy females and patients with
PMDD, exploring its association with 5-HTT availability and
depressive symptom severity. Unlike previous research, we
employed a longitudinal design with robust measures for menstrual
cycle tracking. This thorough approach follows key guidelines for
studying the menstrual cycle,51 enhancing the accuracy and
reliability of our findings within this complex hormonal frame-
work. At the same time, several limitations should be noted. First,
although our design was rigorous, it was conceptualised before
publication of the CAR guidelines,28 which recommended timing
the third CAR measurement at +45 min to best capture the peak.
While this may have reduced temporal precision and potentially
resulted in smaller effect sizes, our decision to push the third sample
to 60 min was, in particular, motivated by previous research related
to the menstrual cycle.13 Recent evidence suggests that this
sampling protocol can still yield reliable CAR estimates compared
with more detailed designs.52 Second, because we focused on
cortisol peaks, it is important to acknowledge that the peak does not
represent a fully dynamic CAR index. Although we controlled for
awakening cortisol levels, the peak itself reflects a stationary
measure. Again, this focus is in line with previous findings of
delayed cortisol peaks in relevant populations.14 Third, our study
included a single CAR assessment per menstrual cycle phase,
although multiple CAR measurements performed on consecutive
days are more reliable.53 However, this single measurement was
suitable for exploring CAR during brief time windows, such as
periovulatory and premenstrual phases, and the timely association
of same-day CAR and 5-HTT measures. To counteract the
potential reduced reliability of a single CAR measurement,
participants were called at each testing day, most salivary samples
were taken under supervision and self-reported delays were
statistically controlled for. Fourth, the diagnosis of PMDD was
based on the Structured Clinical Interview for DSM-519 conducted
by a licensed psychiatrist, complemented by PSST21 assessments at
screening and during the premenstrual phase. While participants
prospectively recorded their mood over 2–3 months, these
recordings did not capture the full daily spectrum of PMDD
symptoms. We acknowledge that daily prospective symptom
tracking over multiple cycles would provide stronger diagnostic
confirmation. Fifth, due to the exploratory nature of the study,
future research on CAR and its relation to the serotonergic system
should focus on cortisol peak as outcome measure and confirm the
findings of the current study. Sixth, because the study was
correlational, we cannot draw definite conclusions about the causal
relationships among cortisol dynamics, serotonergic activity and
depressive symptoms. While we were able to establish a time course
of events due to the longitudinal design, providing important
insights into these associations, further interventional studies
(e.g. manipulating HPA axis response within the menstrual cycle
and/or providing a serotonergic intervention in patients) are
needed to establish causality and clarify the underlying
mechanisms.
This longitudinal study demonstrates attenuated cortisol peaks
in patients with PMDD compared with controls during the
periovulatory phase, as well as underlying associations with the
serotonergic system and the severity of depressive symptoms
during the premenstrual phase. This study characterises PMDD as
a disorder showing alterations in endocrine stress system
regulation.
Kim Hoffmann , Humboldt University of Berlin, Berlin School of Mind and Brain,
Berlin, Germany; Department of Neurology, Max Planck Institute for Human Cognitive
and Brain Sciences, Leipzig, Germany; Cognitive Neurology, University of Leipzig, Leipzig,
Germany; and Centre for Integrated Women’s Health and Gender Medicine, Medical
Faculty, University of Leipzig, Leipzig, Germany; Rachel G. Zsido , Centre for
Integrated Women’s Health and Gender Medicine, Medical Faculty, University of Leipzig,
Leipzig, Germany; and Department of Psychiatry, Clinical Neuroscience Laboratory for
Sex Differences in the Brain, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA; Arno Villringer , Department of Neurology, Max Planck Institute
for Human Cognitive and Brain Sciences, Leipzig, Germany; and Cognitive Neurology,
University of Leipzig, Leipzig, Germany; Swen Hesse , Department of Nuclear
Medicine, University of Leipzig, Leipzig, Germany; Osama Sabri , Department of
Nuclear Medicine, University of Leipzig, Leipzig, Germany; Veronika Engert ,
Institute of Psychosocial Medicine, Psychotherapy and Psychooncology, Jena University
Hospital, Friedrich-Schiller University, Jena, Germany; Julia Sacher , Department of
Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig,
Germany; Cognitive Neurology, University of Leipzig, Leipzig, Germany; Centre for
Integrated Women’s Health and Gender Medicine, Medical Faculty, University of Leipzig,
Leipzig, Germany; and Medical Department III, Endocrinology, Nephrology,
Rheumatology, University of Leipzig, Leipzig, Germany
Correspondence: Julia Sacher. Email: sacher@cbs.mpg.de
First received 31 Oct 2024, final revision 14 Aug 2025, accepted 9 Sep 2025
Supplementary material
The supplementary material is available online at https://doi.org/10.1192/bjp.2025.10432
Data availability
Codes for statistical analyses are available from the corresponding author upon reasonable
request.
Exploring the cortisol awakening response in premenstrual dysphoric disorder
7
https://doi.org/10.1192/bjp.2025.10432 Published online by Cambridge University Press
Acknowledgements
We thank Anne Krieger for helping with the graphic design of Fig. 1.
Author contributions
Conceptualisation: K.H., R.G.Z., V.E., J.S. Methodology: A.V., S.H., O.S., V.E., J.S. Formal analysis:
K.H., R.G.Z., V.E., J.S. Investigation: R.G.Z., J.S. Resources: A.V., S.H., O.S., J.S. Writing (original
draft): K.H., J.S. Writing (review and editing): K.H., R.G.Z., A.V., S.W., O.S., V.E., J.S. Visualisation:
K.H. Supervision: V.E., J.S. Funding acquisition: J.S.
Funding
Funding was provided by Humboldt-Universität zu Berlin, Berlin School of Mind and Brain (to
K.H.), and by DFG (no. 534642099), MPG Brain HATCH Project (Human Cognition Hormones)
and University Medical Centre Leipzig. Open access funding provided by Max Planck Society.
Declaration of interest
None.
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