(2024) 22:346
Liwinski et al. BMC Medicine
https://doi.org/10.1186/s12916-024-03548-z

BMC Medicine

RESEARCH

Open Access

Gender-affirming hormonal therapy induces
a gender-concordant fecal metagenometransition in transgender individuals
Timur Liwinski1†, Matthias K. Auer2,3†, Johanna Schröder4, Ina Pieknik3, Christian Casar5,
Dorothee Schwinge5, Lara Henze5, Günter K. Stalla2,6, Undine E. Lang1, Alina von Klitzing7, Peer Briken7,
Thomas Hildebrandt8, Jeanne C. Desbuleux3, Sarah V. Biedermann9, Paul‑Martin Holterhus10, Corinna Bang11,
Christoph Schramm5,12,13† and Johannes Fuss3*†

Abstract
Background Limited data exists regarding gender-specific microbial alterations during gender-affirming hormonal
therapy (GAHT) in transgender individuals. This study aimed to investigate the nuanced impact of sex steroids on gut
microbiota taxonomy and function, addressing this gap. We prospectively analyzed gut metagenome changes associ‑ated with 12 weeks of GAHT in trans women and trans men, examining both taxonomic and functional shifts.
Methods Thirty-six transgender individuals (17 trans women, 19 trans men) provided pre- and post-GAHT stool sam‑ples. Shotgun metagenomic sequencing was used to assess the changes in gut microbiota structure and potentialfunction following GAHT.
Results While alpha and beta diversity remained unchanged during transition, specific species, including Parabacteroides goldsteinii and Escherichia coli, exhibited significant abundance shifts aligned with affirmed gender. Overall func‑
tional metagenome analysis showed a statistically significant effect of gender and transition (R2 = 4.1%, P = 0.0115),
emphasizing transitions aligned with affirmed gender, particularly in fatty acid-related metabolism.
Conclusions This study provides compelling evidence of distinct taxonomic and functional profiles in the gut micro‑
biota between trans men and women. GAHT induces androgenization in trans men and feminization in trans women,
potentially impacting physiological and health-related outcomes.
Trial registration Clinicaltrials.gov NCT02185274.
Keywords Gender-affirming hormonal therapy, Sex steroids, Microbiome, Microbiota, Metagenome, Trans women,
Trans men, Fatty acid-related metabolism†

Timur Liwinski and Matthias K. Auer share first authorship.

†

Christoph Schramm and Johannes Fuss share last authorship.

*Correspondence:
Johannes Fuss
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom‑mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Liwinski et al. BMC Medicine(2024) 22:346

Background
Transgender individuals experience a mismatch between
their sex assigned at birth and their gender identity [1].
Historically, transgender identities were seen as rare, but
recent data indicate that this population is growing. Current estimates suggest that approximately 0.3 to 0.5% of
adults and 1.2 to 2.7% of children and adolescents identify as transgender [2]. When considering broader gender
diversity, these numbers increase from 0.5 to 4.5% among
adults and 2.5 to 8.4% among younger populations [2].
In the USA, about 1.6 million individuals aged 13 andolder identified as transgender in 2022 [3], with a recent
Pew survey indicating that 5% of adults under 30 identify as transgender or gender non-binary [4]. Transgender individuals frequently face stigma, discrimination,and social exclusion, leading to various health disparities[5, 6]. Seminal studies, such as the Trans PULSE Project,highlight how anti-trans stigma has led to the erasure oftransgender individuals in health research, policy, andpractice [7]. Despite recent increases in global transgender health research, significant gaps remain, particularly
in high-quality studies [8, 9]. One notable gap is researchon gender-specific microbial alterations during genderaffirming hormonal therapy (GAHT), commonly referred
to as hormone replacement therapy (HRT). A large percentage of transgender individuals either use or plan touse GAHT to develop physical traits aligned with their
desired gender, thereby affirming their gender identityand enhancing their mental health and quality of life. In
the 2015 U.S. Transgender Survey, 78% of respondents
desired hormone therapy related to gender transition,but only 49% had ever received it [10]. Gender affirmation is a personalized process and has been associatedwith positive health outcomes, while attempts to alter aperson’s gender identity, such as so-called reparative or
conversion therapy, cause substantial harm [11–14].
The human gut microbiota, consisting of trillions of
microorganisms in the gastrointestinal tract, plays acrucial role in overall health and interacts with almost
every organ system [15]. Research into the relationshipbetween sex-specific microbiota and clinical characteristics is still emerging. Some studies suggest differencesin microbiota composition between genders, but results
have been inconsistent [16–20]. The relationshipbetween sex hormones and gut microbiota is complex
and bidirectional: specific bacteria can influence sex steroid metabolism, while sex steroids may affect microbiota
composition [18, 21–26]. Exploring these interactions
in humans is challenging due to numerous confounding
factors, such as genetic background, which significantly
impacts microbiota composition [27]. Cross-sectional
microbiota studies cannot establish causative relationships, making prospective research essential [28].

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Transgender individuals undergoing GAHT provide a
unique opportunity to study sex steroids’ effects on gut
microbiota, as their chromosomal background remains
stable while they undergo significant hormonal changes.
Investigating the interplay between gender, sex hormones, and microbiota addresses a critical gap in medical
knowledge. Understanding these interactions is vital fordeveloping improved diagnostic and therapeutic strategies for conditions influenced by hormonal status andgut microbiota, such as autoimmune diseases, colorectal
cancer, metabolic syndrome, and mental health disorders [29–32]. Furthermore, research on GAHT’s impact
on gut microbiota could directly benefit transgenderindividuals. The microbiome, often termed the “second
genome,” is crucial in health and disease, correlating withvarious health markers and offering potential therapeutictargets [33–36]. As microbiome research progresses, its
integration into clinical practice is increasing, promising
new insights and interventions [37]. However, transgender individuals remain underrepresented in microbiota
studies, hindering our understanding of how microbiotachanges affect their health [38]. They face higher risks
for various health conditions, including cardiovasculardisease, HIV-related illnesses, cancers, and suicide [39].
Therefore, a multidisciplinary approach is necessaryfor effective transgender healthcare, and primary carepractitioners play a crucial role [14, 40]. With the growing transgender population, there is a pressing need for
healthcare providers to receive education on the complexities of transgender healthcare to ensure equitablecare.
This study presents the results of a prospective investigation into the impact of 12 weeks of GAHT on the gut
metagenome, using metagenomic shotgun sequencing.
It aims to fill the existing knowledge gap by providing acomprehensive analysis of how GAHT affects gut microbiota in trans women and trans men. The findings will
have implications for clinical care and future research,aiming to inform primary care practitioners and specialists involved in transgender healthcare.

Methods
Sex as a biological variableThis study, involving transgender individuals undergoing
gender-affirming hormonal therapy (GAHT), was meticulously designed to consider sex as a critical biologicalvariable. Given the unique nature of the study population,
which includes both trans women and trans men, thefocus inherently involves exploring the impact of GAHT
on individuals assigned female at birth and individuals
assigned male at birth. This approach aligns with the aimof understanding the nuanced effects of sex steroids on
gut microbiota in the context of gender transition. This

Liwinski et al. BMC Medicine(2024) 22:346

design choice recognizes the importance of capturing thediversity of responses based on sex and ensures a comprehensive exploration of microbial alterations associated with GAHT. As such, the findings are anticipated tocontribute insights applicable to individuals across the
biological sex spectrum, enriching our understanding of
the interplay between sex hormones and the gut microbiota in the transgender population.
Study design

The data analyzed here were collected within the“Transgender in Transition” (acronym: Transit) study,
a prospective multicenter observational study aiming at
the assessment of the effects of GAHT on psychological and metabolic endpoints. In this research article, we
focused on analyzing, evaluating, and interpreting a specific aspect of the collected materials, namely the stool
samples. Stool samples were obtained from transgenderindividuals before and 3 months after initiation of GAHT.
Serum hormone levels were measured to confirm effectiveness and compliance with therapy. Food intake wasassessed using a self-constructed item questionnaireobtaining information on all relevant consumed nutrients at each time point (Additional File 1). We analyzed
potential variations in food intake frequency in order tomore precisely delineate the influence of sex steroids on
gut microbiota from potential alterations in dietary patterns that may be associated with the transitional phase.
The present data were collected between June 2014
and September 2021 in four different centers, including
the Endocrinology Department of the Max Planck Institute of Psychiatry in collaboration with the Hormone andMetabolism Center Munich, the Gynecology Departmentof the University Hospital Erlangen, and the Institute for
Sex Research, Sexual Medicine, and Forensic Psychiatryof the University Medical Center Hamburg-Eppendorf.
Study population

The recruitment of participants included in the study was
conducted by the scientific staff and physicians from the
medical departments.
– Inclusion criteria: transsexualism according to ICD10 (F64.0)– Exclusion criteria: age < 18 years, incapacity for legaltransactions due to other reasons, severe medicalcomorbidity, pregnancy, and use of antibiotics within
4 weeks before stool collection
Based on these criteria, we were able to include samples from n = 36 participants in the study, including 17trans women and 19 trans men. No non-binary individuals were included in the study because our center did not

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receive any requests for gender trait-modulating hormonal therapy from non-binary individuals.
Some individuals received psychiatric and/or somatic
diagnoses, which were evenly distributed. Amongtransgender men, depression (F32.9) was the most common diagnosis with four cases, followed by Hashimoto
thyroiditis (E06.3) with two cases. Additionally, there was
one case each of autism (F84.0), asthma (J45.0), ulcerative colitis (K51.9), coronary artery disease (I25.10), irritable bowel syndrome (K58.9), and gastroesophageal
reflux disease (K21.9). For transgender women, depression (F32.9) was diagnosed in two cases, while cholesteatoma (H71.90) and alopecia universalis (L63.0) each had
one case. Anxiety disorder (F41.9) was also diagnosed in
one case among transgender women.
The initial assessment was conducted before the startof GAHT. Clinical data was collected prospectively.
Twelve trans women and 13 trans men returned a completed food item frequency questionnaire before and 3
months after the commencement of GAHT. The collection of blood samples, as well as measurements of bodymass index (BMI), were carried out in the medical centers. Participants were given stool collection tubes with
DNA stabilizer (Invitek Diagnostics, Berlin, Germany).
Follow-up assessments were scheduled 3 months after
the commencement of GAHT. Participants with antibiotic intake within the 3-month study period were notincluded in the analysis.
All participants in the study received standard full
doses of sex steroids. Hormone therapy for trans men
was administered by the responsible endocrinologists
and consisted of either transdermal testosterone gel (25–50 mg testosterone per day), injections of 1000 mg testosterone undecanoate every 12–14 weeks, or testosterone
enanthate 250 mg every 2–3 weeks. The target testosterone levels just before the next injection were within the
mid-range of age-adjusted reference values [41]. Trans
women were treated with either estradiol transdermalgel (1.2–3.6 mg 17b-estradiol per day) or oral estradiol
valerate (2–8mg per day) and oral cyproterone acetate(5–50 mg per day). The goal was to achieve normal or
suppressed luteinizing/follicle-stimulating hormone levels (since participants had not undergone gonadectomy)
with estradiol levels in the mid-follicular range approximately 2 to 4 h after application, as well as testosterone
levels within the female reference range [41].
Hormonal measurements

Serum was obtained by centrifugation at 2000g for 10
min and frozen at − 80°C until further analysis. Quantitative measurement of serum hormone levels was performed using MassChrom Steroid LC–MS/MS Assays(Chromsystems, Germany) by UPLC-ESI–MS mass

Liwinski et al. BMC Medicine(2024) 22:346

spectrometry LCMS-8060 (Shimadzu, Japan). The steroid measurements were carried out at the UKSH in thepediatric endocrinology laboratory at the Department ofPediatrics and Adolescent Medicine I (Kiel, Germany).
The laboratory is accredited according to DIN-ISO
15189.
Stool sample material

After stool sample collection using stool collection
tubes with DNA stabilizer (Invitek Diagnostics, Berlin,
Germany; for kit instructions see Additional File 2) inthe participants’ homes, the samples were immediately
shipped by mail. The samples, taken at room temperature, were cooled to − 80°C upon arrival at the collaborating microbiota laboratory in Kiel and stored until further
processing.

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using Illumina’s bcl2fastq script. To ensure data quality, reads were trimmed using Trimmomatic. To remove
host reads, bowtie2 (v2.3.5.1) was employed against the
GRCh38 human reference genome. Taxonomic assignment of bacterial DNA was performed using Kraken2(v2.1.3) against the Genome Taxonomy Database, relying
on the exact alignment of k-mers. Bayesian re-estimationof bacterial abundance was carried out using Bracken(v2.8). Bacterial taxa with a total abundance of less than
0.001% were excluded. For functional annotation, the
Humann3 pipeline was utilized, using the same input
reads as for the taxonomic analysis. The output tables
were normalized to relative abundances, combined, andannotated to gene families based on UniRef protein clusters (90% identity), as well as to the Kyoto Encyclopediaof Genes and Genomes (KEGG) and Gene Ontology(GO) terms.

DNA extraction

DNA extraction was performed using the QIAamp Fast
DNA Stool Mini Kit (Qiagen, Hilden, Germany) on the
QIAcube automated system. Approximately 200 mg ofstool sample was transferred to 0.70-mm Garnet Beadtubes, which were filled with 1.1 ml of ASL lysis buffer(containing proteinase K). Subsequently, the cells werelysed using bead-beating as the cell disruption method,where cell suspensions in reaction vessels are disrupted
by small glass beads through mechanical effects. The
homogenizer SpeedMill PLUS was used for 45 s at 50
Hz for this purpose. Afterward, the samples were heatedat 95°C for 5 min. The purification of the sample was
ensured by the QIAamp silica membrane, which allows
for the passage of impurities while specifically binding
the DNA. PCR inhibitors were removed using an optimized buffer. The amount of extracted DNA ranged from
1 to 10 µg per sample.
Shotgun metagenomic analysis

Shotgun metagenomic analysis was conducted on thesamples. Instead of focusing solely on individual genes
like those responsible for ribosomal RNA (rRNA) togenerate taxonomy-based “16S rRNA profiles,” shotgun
metagenomic sequencing encompasses the sequencingof the entire metagenome of microbial communities. In
contrast to 16S sequencing, which offers limited taxonomic information, shotgun metagenomic sequencing(MGS) of the stool microbiome provides comprehensive
insights into both taxonomic composition and functional
attributes [37]. This approach has demonstrated significant promise in terms of diagnostic utility [37].
The Illumina DNA Prep Library Preparation kit protocol was followed for sample preparation, and sequencing
was performed on the NovaSeq Platform using 2 × 150
bp paired-end reads. The fastq files were generated

Statistics

All statistical analyses were performed using the R software (v3.5.1). Normality was assessed employing the Shapiro test. In instances of normally distributed data among
independent samples, the Welch t-test was employed,
while non-normally distributed data was subjected to
the Wilcoxon test. The examination of food frequency
data involved a repeated-measures two-way analysis ofvariance (ANOVA) utilizing the R stats aov function,
incorporating an interaction term for time and type oftransition.
To assess within-sample diversity (α-diversity), we
calculated Shannon entropy based on a Hellinger-transformed abundance matrix using the “vegan” package(v2.5.6) functions “decostand” and “diversity” [42]. We
employed the F-test to compare variances of the Shannon index. Additionally, we employed a generalized additive mixed model to test for the statistical significanceof differences in alpha diversity, utilizing the “mgcv” R
package, version 1.9–0 [43]. This approach was chosen toaccount for repeated measurements and random effects
arising from multiple assessments of the same patient.
The regression estimate (β) ± and the standard error (SE)are reported.
For evaluating between-sample diversity (β-diversity),
we used Bray–Curtis dissimilarity on Hellinger-transformed species abundance and metabolic pathway relative abundance matrices. The statistical significance ofseparation among groups was assessed using permutational multivariate analyses of variance (PERMANOVA).
Pairwise multilevel comparisons with PERMANOVA,
while considering repeated measures, were conductedemploying the ’pairwiseAdonis’ function (https://​github.​com/​pmart​ineza​rbizu/​pairw​iseAd​onis).

Liwinski et al. BMC Medicine(2024) 22:346

Differences in individual bacterial species were tested
using the generalized additive mixed model (GAMM;“mgcv” package, version 1.9–0) on the untransformed
count data matrix, with library size as an offset, assuming
a negative binomial distribution. The same models were
employed to test for differences in the distribution of single pathways, assuming a Gaussian distribution.
To assess the predictive capability of the previously
identified sex-associated species, predictive modeling
was performed using a generalized linear model with the“rms” package (version 6.7–1), and the c-statistic (areaunder the receiver operating characteristic curve) was
calculated to evaluate model performance.
For predicting clinical phenotypes based on single species-level and pathway-level abundances, we employeda method known as “selbal” [44]. This method operates with microbial balances, which are ratios of taxonomic quantities, allowing for feature selection andclassification or regression while accounting for thecompositional nature of microbial sequencing data andcontrolling for confounders. We used threefold crossvalidation to obtain reliable results for each selbal model,
and the area under the receiver operating characteristic curve (AUROC) was reported to assess classification
performance.
The within-subject design enabled participants to serveas their own controls, thereby controlling for a range ofknown confounders that could potentially impact gut
microbiota composition, such as age, metabolic status,
lifestyle factors, comorbidities, medications, and diet.
Additionally, we assessed dietary habits to ensure theyremained consistent throughout the observation period.
P-values were generally considered significant whenP < 0.05 and were adjusted for the false discovery rate(FDR) when necessary.
Study approval

The study was approved by local ethics committees andis additionally registered in the US clinical trials registry

Page 5 of 16(clinicaltrials.gov NCT02185274). It adheres to the ethical guidelines of the Helsinki Declaration of 1964 and its
latest revision in 2013, as well as the STROBE Statement[45]. All participants were provided with information
about the voluntary nature of participation, and writtenconsent was obtained from all included subjects.

Results
Demographic, clinical, and dietary profile

In total, high-quality metagenomic samples from bothtime points, baseline (BL) and 3 months after transition
initiation (M3) were available for n = 36 participants.
Overall, 19 individuals underwent the transition fromfemale to male hormonal phenotype (trans men) and 17
participants transitioned from male to female hormonal phenotype (trans women) (Table 1). As anticipated,
there were alterations in sex hormone levels observed
from baseline to 3 months following GAHT (Additional
File 3: Fig. S1A-F). No significant adverse effects werereported, such as vomiting, constipation, diarrhea, significant weight loss or gain, thrombosis, serious moodchanges, recurrent hot flashes, or severe headaches. Analyzing the food frequency questionnaire data, no discernible changes were observed in any food item concerningtransition time point and transition type (all FDR > 0.1).
This suggests that potential alterations in the microbiota
are not attributable to significant dietary shifts during thetransition period.
Changes in gut microbial diversity in response
to gender‑affirming therapy

We employed a GAMM to evaluate the effects of various
factors, including transition type, time point, and theirinteraction, on alpha diversity (within-sample diversity),
as measured by the Shannon index. Our analysis did not
find significant differences in alpha diversity when considering the factors of transition type (β =  − 0.12 ± 0.10,
P = 0.2672), time point (β =  − 0.16 ± 0.09, P = 0.0918),
or their interaction (β = 0.19 ± 0.14, P = 0.1628; Fig. 1A).

Table 1 Demographic, clinical, and behavioral characteristics of the study participants included in the microbiota analysis
Variable

Transgender women(MTF; n = 17)

Transgender men(FTM; n = 19)

P-value

Age, years (mean, SD)

48.0 ± 17.2

24.4 ± 8.9

0.034

Body mass index, kg/m2 (mean, SD)

22.7 ± 3.5

23.7 ± 4.0

0.927

12 (70.6)

NA

Hormone therapy (n, %)Variable category

Cyproterone acetate
Estrogen/estradiol

17 (100)

NA

Finasteride

2 (11.8)

NA

Testosterone gel (transdermal)NA

6 (31.6)

Testosterone undecanoateNA12 (63.2)

Testosterone enanthateNA

1 (5.3)

Liwinski et al. BMC Medicine(2024) 22:346

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Fig. 1 Changes in fecal microbiota composition in people with gender-affirming hormonal care. The figure shows the alpha (A) and beta (B)diversity, alongside the relative abundance distribution (Hellinger transformed) of species that exhibit statistically significant differential abundance(FDR < 0.05; C–F) between baseline (BL) and 3 months of gender-affirming hormonal care (M3). BL baseline, M3 3 months after commencementof gender-affirming hormonal care, TM trans men, TW trans women

We assessed alterations in the variance of alpha diversity over time within two distinct groups: trans men andtrans women. Our findings revealed a significant increasein the variance of the Shannon index within trans men(F = 0.22, P = 0.0024). c 3 months following the initiationof hormonal treatment (F = 1.22, P = 0.6941; Fig. 1A).

Liwinski et al. BMC Medicine(2024) 22:346

This disparity in variance dynamics suggests differential
responses to GAHT in these two distinct populations
with regard to the alpha diversity of their gut microbiota.
We proceeded to examine the potential response ofbeta diversity (between-sample diversity) to GAHT. Following confirmation that the assumption of multivariate
homogeneity of group dispersions (variances) was not
violated (betadisper, F = 1.04, P = 0.3788), we conductedpairwise multilevel comparisons with PERMANOVA
while considering repeated measures. Our analysis did
not reveal a discernible overall effect of time (R2 = 2.16%,
P = 0.0622), transition type (R2 = 1.1%, P = 0.0602), or
their interaction (R2 = 1.7%, P = 0.1979) on microbiota
composition (Fig. 1B). These results indicate that, within
the scope of this study, there were no significant alterations in taxonomic beta diversity associated with GAHT
over time or in relation to different transition types.
Sex‑dependent variations in bacterial species abundance
following hormonal treatment

We proceeded with the analysis of changes in the relative abundance of individual bacterial species over thecourse of 3 months of GAHT. Following the applicationof the FDR, our investigation revealed four bacterial
species that exhibited varying relative abundance patterns in relation to both the type of transition and time
(Fig. 1C–F). These four species are as follows: Parabacteroides goldsteinii (β = 2.25 ± 0.64, FDR = 0.0264), Coprococcus sp. ART55/1 (β = 3.75 ± 0.78, FDR = 3 × ­10–4),
Coprococcus eutactus (β = 2.16 ± 0.63, FDR = 0.0289), andEscherichia coli (β =  − 4.2 ± 0.99, FDR = 0.0019). Remarkably, in the case of these four bacterial species, we noted a
distinctive pattern that aligns with the current sex steroid
phenotype (pre- and post-transition) of the individuals.
For instance, Escherichia coli exhibit on average a higher
relative abundance in both trans women before hormonal therapy and trans men after hormonal therapy (i.e.,a male-typical sex steroid phenotype), while displaying
lower abundance in pre-transition trans men and posttransition trans women (i.e., a female-typical sex steroid
milieu). Conversely, the Coprococcus species demonstrated a higher abundance in participants with a femaletypical sex hormonal phenotype and a lower abundance
in a male-typical hormonal phenotype, reflecting a notable association with hormonal sex state.
Bacterial abundance predicts hormonal sex

In order to evaluate the predictive capability of the previously identified sex steroid-associated species, we conducted predictive modeling utilizing a generalized linear
model. In this model, we treated current hormonal sex
phenotype as a binary variable and employed the four
species as predictor variables. Specifically, we compared

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pre- and post-transition female with pre- and post-transition male-typical hormonal phenotypes. Our analysis
involved the following steps: initially, we fitted the fullmodel, and subsequently, we conducted a grid search todetermine the optimal penalty value. To obtain an outof-sample estimate of model performance, we employedbootstrap resampling. The resultant c-statistic, with avalue of 0.77, indicates a good discriminatory ability ofthe model. Furthermore, the calibration curve demonstrates that the predictions closely align with the ideal
predictions across the entire spectrum of predicted values (Fig. 2A).
We adopted an alternative predictive methodologythat involved the inclusion of all accessible bacterial species, following an initial filtration step. In this approach,
we employed the Selbal algorithm, which applies a forward-selection technique to identify two distinct groupsof taxa. The focus was on taxa whose relative balanceis associated with the response variable of interest. The
Selbal analysis pinpointed a noteworthy shift in balances,which are essentially ratios of genus relative abundances.
Specifically, the shift was observed between Escherichia coli, representing the numerator and indicative of
male-typical sex hormone phenotype, and Bacteroides
luhongzhouii, serving as the denominator and indicative of female-typical sex hormone phenotype (Fig. 2B).
The observed shift in balance effectively discriminates
between female and male individuals, achieving an
area under the receiver operating characteristic curve(AUROC) of 79.6% (Fig. 2C).
Alterations in microbial functionality in response
to gender‑affirming hormonal treatment

We conducted an in-depth analysis of the comprehensivefunctional metabolic capacity by examining the entire
bacterial metagenome through the HUMAnN framework. Our analytical approach involved performing pairwise multilevel comparisons utilizing PERMANOVA
while accounting for repeated measures. In the courseof our investigation, we identified noteworthy associations in terms of overall functional metagenomic variation. Specifically, we observed that the sex assigned atbirth (R2 = 1.7%, P = 0.0398) displayed significant associations with the functional metagenomic profile. Furthermore, our analysis revealed a statistically significant
effect (R2 = 4.1%, P = 0.0115; Fig. 3A) associated with theinteraction between transition type and time on the overall functional metagenome. Principal coordinate 1 (PC1),
which captured most of the variation (32.92%), revealed aseparation pattern that aligns with the current sex steroid
phenotype (pre- and post-transition) of the individuals(F = 8.0, p = 0.0078; Fig. 3A). This finding underscores theinfluence of GAHT in inducing changes within the gut

Liwinski et al. BMC Medicine(2024) 22:346

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Fig. 2 Ability of fecal microbiota composition to predict sex hormone phenotype. A The outcomes of predictive modeling employing
a generalized linear model for distinguishing between the male-typical (MHP) and the female-typical sex hormone phenotype (FHP). The
calibration curve demonstrates accurate predictions throughout the spectrum of predicted values. B Presentation of the global balance
concerning the hormonal sex phenotype. The box plot illustrates the distribution of balance scores for female and male-typical hormonal
phenotypes, specifying the two taxa groups constituting the global balance along with their respective density curves. C Depiction of the ROC
curve accompanied by its corresponding AUC value (0.796). FHP male-typical hormonal phenotype, MHP male-typical hormonal phenotype

metagenome that align with the desired characteristics ofthe affirmed gender.
In order to pinpoint the pathways that exhibit alterations corresponding to hormonal sex status across thetransition period, we employed the GAMM framework.
Out of the 500 pathways identified by HUMAnN 3.0, a
substantial portion, namely 184 pathways (representing
36.8% of the total), displayed differential abundance patterns. Following the application of FDR correction, ouranalysis unveiled that 125 pathways (25% of all pathways)
exhibited a significant association with the process oftransition (Additional File 4). This underscores the substantial extent of functional changes that are linked tohormonal sex status. Within this set, nine pathways demonstrated particularly robust associations with transition,

as indicated by FDR values < 0.001 (Fig. 3B–J). Notably,
akin to the single species analysis conducted earlier, allof the most prominent pathway hits’ average abundancevalues align with the characteristics of the target sex phenotype, further emphasizing the significant influence ofhormonal sex milieu on the functional metabolic capacity of the microbiota.
In our attempt to further refine and focus on potentiallypivotal alterations in pathways, we employed the Selbal
methodology, which specifically examines the conceptof balances within pathway data. This analysis led to theidentification of an optimal discriminatory set consisting of three pathways, effectively distinguishing between
individuals of both female- and male-typical hormonal
phenotype (comprising both pre and post-transitional

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Fig. 3 Metabolic pathway analysis. A The biplot visually represents the metagenomic functional beta-diversity; the graph shows a clear separation
along the first principal coordinate (PC1), which captured most of the variation (32.92%). B–J Display of individual metagenomic pathways
with statistically significant differential abundance at an FDR level < 0.001. BL baseline, M3 3 months after commencement of gender-affirming
hormonal care, TM trans men, TW trans women, **p < 0.01; *p < 0.1; ns not significant; significance levels are indicated for post hoc paired t-tests

sexual hormonal statuses). Notably, among these pathways, “chitin derivatives degradation” and the “superpathway of ornithine degradation” emerged as characteristicfeatures associated with the female group, while “fatty
acid and beta oxidation IV” was identified as the hallmark of the male group. The balance observed among
these three pathways exhibited a considerable discriminatory capacity, yielding an impressive area under the
curve (AUC) of 83.8% (Fig. 4).

Discussion
This study reveals significant gender-concordant changes
in the taxonomic composition and metabolic capacity of
fecal microbiota in a cohort of trans women and transmen undergoing GAHT. Previously, there was some evidence that sex might exert an influence on the diversity,
composition, and function of the gut bacterial microbiota, although the findings have been inconclusive. Early
investigations, involving a relatively small sample size andconstrained by limited technological capabilities, yielded
minimal to no discernible gender-related distinctions.

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Fig. 4 A Discriminatory capability of metabolic pathways for sex hormone status. Visualization of the global balance pertaining
to the metagenomic functional hormonal sex phenotype. The box plot delineates the distribution of balance scores for female-typical (FHP)
and male-typical hormonal phenotypes (MHP), identifying the two pathway groups composing the global balance, and providing their respective
density curves. B ROC curve with its associated AUC value (0.838). FHP male-typical hormonal phenotype, MHP male-typical hormonal phenotype

For instance, a 2005 study involving 91 individuals ofnorthern European descent (from France, Denmark,Germany, the Netherlands, and the UK) did not reveal
any significant variations in gut microbiota between thesexes, as determined by principal component analysis[46]. In a 2008 Chinese study employing group-specificdenaturing gradient gel electrophoresis (DGGE) profiling of Bacteroides species, a greater prevalence of Bacteroides thetaiotaomicron was observed in men [47].
Recent extensive population-wide studies have similarly
not demonstrated significant sex-specific variations in
the diversity, intricacy, or composition of gut microbiota[16, 48]. Nevertheless, these initial studies were methodologically limited, mainly due to the absence of shotgun
metagenomic sequencing in most of them. In a substantial cohort study encompassing two independently wellcharacterized groups, namely the Belgian Flemish Gut
Flora Project (consisting of 1106 individuals) and theDutch LifeLines-DEEP study (comprising 1135 individuals), sex exhibited a relatively minor effect size among the
69 factors that were found to be significantly associatedwith the overall variation in the microbiota [49]. In a large
Dutch research study employing metagenomic shotgun
sequencing and after accounting for multiple variables,
the only discernible association with sex was related to
Akkermansia muciniphila, where women were observed
to have a higher prevalence of this particular species[50]. Nevertheless, the outcomes of each study pertaining to variations in microbial taxa between the sexes display inconsistencies [50–53]. This lack of consistency is

to be expected, given the myriad potential confounding
variables and the multitude of factors related to sex andgender identity that can impact the microbiota, extending beyond the influence of sex steroids [49]. It is worth
noting that many of these studies did not factor in menopausal status, which signifies a pivotal juncture in a woman’s life cycle marked by profound hormonal changes.
Therefore, precious evidence is furnished by a study
encompassing both pre and post-menopausal women, as
well as men [18]. This study demonstrated that the gut
microbiota of post-menopausal women exhibited greater
similarity to that of men rather than pre-menopausal
women [18]. Comprehensive analyses of metagenome
functionality unveiled no significant disparities between
post-menopausal women and men [18]. These findings
underscore the impact of sex-specific hormonal status in
shaping sex-specific patterns within the gut microbiota.
Nonetheless, due to the cross-sectional design and theabsence of a longitudinal within-subject approach with ahigh degree of covariate stability, this study cannot definitively assert that the observed changes are exclusively
linked to sex steroid status. Accumulating evidence suggests that the gut microbiota may play a significant rolein determining the timing of puberty through its metabolic and hormonal effects [54]. However, data on the gut
microbiota of human adolescents are limited. Korpela
et al. demonstrated that the gut microbiota shifts towards
an adult-like composition as puberty progresses, indicating a potential association between sex hormones andgut microbiota development. Unfortunately, the lack ofLiwinski et al. BMC Medicine(2024) 22:346

hormone level measurements and reliance on 16S rRNA
gene sequencing in this study limits direct comparability
with our findings [55].
Our results suggest that GAHT induces specific transitional changes in bacterial species that align with thedesired gender features. This notably pertains to thespecies Parabacteroides goldsteinii, Coprococcus sp.
ART55/1, Coprococcus eutactus, and Escherichia coli.
Coprococcus species inhabit the human colon and arestrictly anaerobic bacteria [56]. More pronounced alterations in the gut metagenome became evident in response
to GAHT when we analyzed metagenomic functionality. This analysis revealed significant variations in boththe overall composition and a multitude of individual
metabolic pathways. Remarkably, among the pathways
exhibiting a stronger association with the male hormonal
phenotype, several functions related to lipid metabolism
were identified. These included processes such as palmitate biosynthesis, unsaturated fatty acids biosynthesis(predominantly by E. coli), and fatty acid and beta oxidation IV. While considerable focus has been directed
towards investigating the short-chain fatty acid metabolism of the gut microbiota, substantially less researchhas been undertaken to elucidate the importance of its
anabolic and catabolic metabolism of medium- and longchain fatty acids [57]. The majority of research examining
the interplay between dietary lipids and the microbiota
is derived from rodent studies. However, these investigations are inherently constrained by the fundamental disparity in nutritional requirements between humans andmice [57].
Transgender and gender-diverse patients encounter
numerous barriers to medical care, with a 2019 systematic review indicating that 27% (range, 19–40%) had beendenied care by a healthcare professional [9]. Despiteongoing barriers, the knowledge base on transgender
healthcare has expanded in recent years and is a rapidly advancing interdisciplinary field [14, 58, 59], The
World Professional Association for Transgender Health(WPATH) recognizes that GAHT, while offering benefits
such as reduced depression and anxiety, is also associatedwith gender-specific risks that require consideration during and after transition [58]. There is a well-recognizedsexual dimorphism in the risk of various common diseases. Notably, men and postmenopausal women exhibit
an elevated cardiometabolic risk in contrast to premenopausal women [60]. A recent meta-analysis revealed thattransgender individuals exhibit a 40% increased risk ofcardiovascular disease in comparison to cisgender individuals of congruent birth sex [61]. Individuals assigned
female at birth and presently identifying as transgenderexhibited 2.66 times higher odds of cardiovascular disease in comparison to those identifying as cisgender [62].

Page 11 of 16

The importance of both sex steroids and gut microbiota
in cardiometabolic health is well established [63]. Various
bacterial metabolites within the intestinal tract, encompassing toll-like receptor agonists, short-chain fatty acids(SCFAs), and secondary bile acids, exert direct influence
on metabolic functions such as insulin sensitivity, alongside immune-mediated metabolic impacts [64]. Humanstudies have revealed the pivotal role of gut microbiota
composition and microbial metabolites in predicting
major adverse cardiovascular events (MACE) as well as
the metabolic and inflammatory alterations preceding
MACE [65, 66]. In our study, we found a gender congruent decline of C. eutactus in trans men. C. eutactus, asa significant producer of butyrate, exhibits firmly established anti-inflammatory properties [67, 68]. Its protective role in glucose homeostasis and insulin sensitivity[69, 70], its association with longevity in centenarians[71], and its potential role in enhancing exercise capacity [72] suggest that it could serve as a pivotal beneficial commensal for promoting cardiometabolic health.
Therefore, it can be hypothesized that the decline of C.
eutactus and potentially other microbiota alterations
could be associated with an increased cardiovascularrisk in transgender men. These taxonomic findings aresupported by multiple alterations in microbiota lipid
metabolism during GAHT in our cohort, providing further insights into the implications of microbiota-lipid
interactions on body composition, insulin sensitivity,
inflammation, and cardiovascular disease risk. Moreover, C. eutactus is acknowledged for its neuroprotective
potential [68]. Notably, C. eutactus has consistently beenfound to be reduced in individuals with Parkinson’s disease (PD), a neurodegenerative movement disorder that
affects men more frequently than women [68]. Estrogenis traditionally regarded as a protective factor against PD.
Estrogen therapy in postmenopausal cisgender women isassociated with a reduced risk of developing PD, and lowdose oral estrogen therapy in postmenopausal cisgenderwomen with PD has demonstrated efficacy in alleviating
motor symptoms [73]. Deeb and colleagues suggest that
GAHT may influence both motor and non-motor symptomatology in movement disorders, advocating for the
expansion of sexual and gender minority research in thisfield. Alterations in the abundance of C. eutactus during
GAHT may offer a connection between hormonal levels
and PD. Another well-recognized concern in transgender healthcare is the potential for GAHT to increase therisk of hormone-sensitive cancers. Testosterone may
promote the formation of colorectal adenomas throughunknown mechanisms, potentially explaining theobserved higher susceptibility to colorectal cancer (CRC)
in men [74]. Among the various factors that may contribute to CRC, E. coli strains, particularly those producing

Liwinski et al. BMC Medicine(2024) 22:346

colibactin from their polyketide synthesis (pks) locus,
have now been identified as potential contributors [75].
We observed a gender-concordant increase of E. coli intransgender men. This could potentially elevate their
future risk of developing CRC. Currently, no studies haveinvestigated the CRC rate in transgender men comparedto cisgender men. However, it is known that transgender individuals utilize the recommended CRC screening
less frequently than cisgender individuals [76], whichis concerning. Driven by rapid technological advancements, there is a burgeoning interest in leveraging the
gut microbiota as both an early indicator of impending
disease and a modifiable risk factor amenable to finely
tuned therapeutic interventions targeting the microbiota,
such as prebiotics, bacteriophages, bacterial metabolites,and engineered probiotics [77]. Our results demonstrategender-congruent alterations in specific bacterial species
that are strongly associated with diseases exhibiting clear
gender predisposition, supported by multiple lines of evidence. Since the advent of the NGS revolution, a significant portion of studies has focused either on descriptive
analyses in humans or, when intervention was pursued,on animal models. However, in recent years, randomized
controlled trials (RCTs) in humans have emerged, providing evidence that microbiota-targeted therapeutics
hold great potential for translation into clinical practice.
Specifically, with regard to C. eutactus, an RCT utilizing galacto-oligosaccharides (GOS) to expand C. eutactus among other butyrate producers has demonstrated
a reduction in symptoms among patients with lactose
intolerance [78]. This illustrates how, in the future,gut microbiota biomarkers could be utilized for posttransition health monitoring or as targets to mitigate
modifiable disease risks associated with GAHT throughprecision microbiota therapeutics.
There is a longstanding hypothesis that the intestinal
microbiota influences systemic estrogen levels [79–83].
Microbial–mammalian symbioses frequently exist withincomplex, co-evolved functional systems that provide
mutual benefits. In the intestines, symbiotic bacteria
express β-glucuronidase enzymes, which can remove theinactivating glucuronic acid from glucuronidated compounds to use as a carbon source [84]. These bacteria
can either further metabolize the parent compound or
release it into the gastrointestinal lumen. Compounds
that were previously glucuronidated and subsequently
reactivated by gastrointestinal microbial β-glucuronidase
enzymes can be reabsorbed into the plasma andundergo cycles of enterohepatic recirculation [85].
β-glucuronidase activity influences levels of non-ovarian
estrogens via this enterohepatic circulation, supporting the hypothesis that decreased β-glucuronidase levels
might increase systemic estrogen levels [86]. Conversely,

Page 12 of 16

intestinal β-glucuronidase activity can respond to alterations in female sex hormone status, as evidenced by studies using murine ovariectomy models [87]. Interestingly,
our study found that an increase in E. coli, a major sourceof intestinal β-glucuronidase [88], was strongly associated with androgenization and decreased with feminization, suggesting a potential role in hormonal phenotypetransition.
The significance of our study transcends the specificpopulation of transgender individuals undergoing GAHT.
The findings provide insights into how hormonal treatments, in general, can influence gut microbiota. This has
implications for various medical conditions and treatments that involve hormone therapy, such as menopause,andropause, and hormone replacement therapy in cisgender individuals [89, 90]. The gut microbiota is known
to play a pivotal role in systemic health, influencing
immune function, metabolism, and even mental health[91]. By elucidating the specific changes in gut microbiota induced by GAHT, our study contributes to a broader
understanding of how hormonal fluctuations can affectthese critical aspects of health. Our research supports themove towards personalized medicine by highlighting theneed for tailored healthcare approaches based on individual hormonal profiles and microbiota compositions.
What remains unclear in human trials designed likeours are the mechanisms by which hormonal alterations
might influence gut microbiota composition and function. One intriguing hypothesis is that hormonal alterations affect gut transit time. Accumulating evidence
suggests that gut transit time is a key factor in shaping
the composition and activity of the gut microbiota [92].
Human reproductive hormones influence gastrointestinal transit time. In a seminal study conducted by Waldet al., it was demonstrated that during the luteal phase,characterized by heightened progesterone levels, there
was a notable prolongation of gastrointestinal transit
time compared to the follicular phase [93]. Notably, areciprocal relationship between gut transit time and sex
steroids appears evident, as elucidated in a human experimental trial wherein pharmacologically induced deceleration of transit time led to a reduction in estrogen levels[94]. Among the differentially abundant taxa observed inour study were Coprococcus spp., which are recognized
as indicative of prolonged gut transit time [92]. Future
investigations concerning the interplay between human
sex hormones and the microbiota should incorporate
assessments of gut transit time.
Emerging evidence indicates that bidirectional gut–brain signaling constitutes a communication pathwaythat utilizes neural, hormonal, and immunological mechanisms to regulate homeostatic processes [95]. Currently, this bidirectional communication is somewhat

Liwinski et al. BMC Medicine(2024) 22:346

overlooked, as most research emphasizes the pathway
from the microbiota and gut to the brain, such as the roleof gut-derived inflammatory signals in the developmentof psychopathology [96]. Based on recent high-quality
evidence from both clinical data and murine models,
it has been demonstrated that psychological factors,
notably psychological stress, can significantly impact
gut homeostasis [97, 98]. Therefore, it is a compelling
hypothesis to investigate how the substantial psychological experiences associated with the initial transition
period might contribute to the reshaping of gut andmicrobiota homeostasis.
Our study has limitations that warrant consideration. First, the sample size was relatively small and heterogenous with regard to delivery of GAHT (e.g., oral
vs. transdermal estradiol), which restricted our ability
to comprehensively explore potential covariates. Second, recognizing the potential advantage of incorporating similarly processed cisgender controls to establish abaseline for sex-specific microbiota patterns, our study’s
exclusive reliance on participants before GAHT potentially restricts the generalizability of our findings. Third,
since our study did not include a control group receiving
placebo instead of GAHT, we are unable to definitively
prove that the observed changes in gut microbiota within
our cohort occurred exclusively due to alterations in thesex hormone phenotype. However, due to ethical considerations, implementing such a study design will remain
untenable in the future as well. Future research should
also aim to expand the functional analysis by incorporating both bacterial and host metabolomes. This study
focused on trans women and trans men. Contrary to
the common assumption that non-binary individuals do
not pursue GAHT, recent evidence, such as an Australian survey, indicates a 77.3% demand for GAHT among
non-binary individuals [99]. Future research should also
examine the implications of GAHT on the gut microbiota
in non-binary individuals.

Conclusions
In conclusion, our findings demonstrate significant differences in the taxonomic and functional profiles of thegut microbiota based on sex hormone profiles. We propose that GAHT leads to the androgenization of the
microbiota in trans men and the feminization of the
microbiota in trans women, potentially bearing consequences for physiological and health-related outcomes.
Abbreviations
ANOVA	Analysis of variance
AUROC	Area under the receiver operating characteristic curve
BL	Baseline
BMI	Body mass index
CRC​	Colorectal cancerDNA	Deoxyribonucleic acid

Page 13 of 16

DGGE	Denaturing gradient gel electrophoresis
FDR	False discovery rate
GAHT	Gender-affirming hormonal treatment
GAMM	Generalized additive mixed modelGO	Gene Ontology
GOS	Galacto-oligosaccharidesHIV	Human immunodeficiency viruses
HRT	Hormone replacement therapy
ICD-10	International Classification of Diseases, 10th Edition
KEGG	Kyoto Encyclopedia of Genes and Genomes
MACE	Major adverse cardiovascular events
PCR	Polymerase chain reaction
PD	Parkinson’s disease
PERMANOVA	Permutational multivariate analyses of variance
RCT​	Randomized controlled trial
rRNA	Ribosomal ribonucleic acid
SCFAs	Short chain fatty acids
SE	Standard error
STROBE	
Strengthening the Reporting of Observational Studies in
Epidemiology
WPATH	World Professional Association for Transgender HealthSupplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12916-​024-​03548-z.
Additional file 1. Dietary questionnaire in both German and English trans‑
lations used in the study.
Additional file 2. Kit instructions for the stool collection tube.
Additional file 3: Fig. S1. Hormonal changes in response to GAHT. The
serum hormone levels (in nmol/L) before and 12 weeks after the initia‑
tion of GAHT in trans women and trans men are displayed, including(A) Testosterone, (B) Androstenedione, (C) Dehydroepiandrosterone, (D)Dihydrotestosterone, (E) 17-Hydroxyprogesterone, and (F) Estradiol.
Additional file 4. Tabular overview of the GAMM results for all 500 micro‑bial metabolic pathways identified by HUMAnN 3.0 in the HMP Unified
Metabolic Analysis Network, including estimates, standard errors, p-values,and FDR-corrected p-values for the interaction between transition time
point and gender.
Acknowledgements
We extend our gratitude to the team at the IKMB Microbiome Laboratory
for their invaluable assistance in handling the stool samples. This researchreceived support from the DFG Research Infrastructure NGS_CC (project407495230), a component of the Next Generation Sequencing Compe‑
tence Network (project 423957469). The NGS analyses were conducted at
the Competence Centre for Genomic Analysis in Kiel. We would also like toextend a special acknowledgment to all study participants for their invaluable
contribution.
Authors’ contributions
The study was conceptualized by Johannes Fuss (JF), Timur Liwinski (TL),
Matthias K. Auer (MKA), and Christoph Schramm (CS). Funding acquisition was
carried out by JF, CS, Peer Briken (PB), MKA, Undine E. Lang (UEL), and Corinna
Bang (CB). Patient support during enrollment and data collection were
provided by MKA, Johanna Schröder (JS), Ina Pieknik (IP), Günter K. Stalla (GKS),
Alina von Klitzing (AK), JF, Jeanne C. Desbuleux (JCD), Sarah V. Biedermann(SVB), and Thomas Hildebrandt (TH). Data analysis was performed by TL, who
also co-authored the original manuscript draft with MKA. Next-generation
sequencing was conducted by CB, with Christian Casar (CC) assisting in bioin‑
formatic analysis. Dorothee Schwinge (DS) and Lara Henze (LH) carried out thehormonal measurements using the technology and infrastructure provided
by Paul-Martin Holterhus (PMH). JF and CS jointly supervised the project. All
authors contributed to the final draft and provided critical comments. All
authors read and approved the final manuscript. Accounting for the order of
co-first authors: In this study, TL assumes the lead authorship due to his instru‑
mental role in guiding the data analysis process and taking a primary role inLiwinski et al. BMC Medicine(2024) 22:346

Page 14 of 16

crafting the initial manuscript draft, reflecting a distinct leadership contribu‑
tion to the intellectual development of the research.
Funding
Open Access funding enabled and organized by Projekt DEAL. Stool sample
processing and sequencing received infrastructure support from the DFG
Excellence Cluster 2167 “Precision Medicine in Chronic Inflammation” (PMI)
and the DFG Research Unit 5042 “miTarget.” Additionally, the study was finan‑cially supported by the Deutsche Forschungsgemeinschaft, DFG (German
Research Foundation), under grant number 42919110.
Availability of data and materials
The original NGS data and meta data can be obtained by making a reasonable
request to the corresponding author. The code to reproduce the results ispublicly available on GitHub (https://​github.​com/​Gavag​uy/​Trans​gender).

Declarations
Ethics approval and consent to participate
The study was approved by local ethics committees and is additionallyregistered in the US clinical trials registry (clinicaltrials.gov NCT02185274). It
adheres to the ethical guidelines of the Helsinki Declaration of 1964 and its
latest revision in 2013, as well as the STROBE Statement [45]. All participants
were provided with information about the voluntary nature of participation,
and written consent was obtained from all included subjects.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Author details
1
Clinic for Adult Psychiatry, University Psychiatric Clinics, University of Basel,
Wilhelm Klein‑Strasse 27, Basel CH‑4002, Switzerland. 2 Medizinische Klinik
and Poliklinik IV, Klinikum der Universität München, LMU München, Munich,Germany. 3 Institute of Forensic Psychiatry and Sex Research, Center for Transla‑
tional Neuro‑ and Behavioral Sciences, University of Duisburg-Essen, Alfredstr.
68‑72, Essen 45130, Germany. 4 Department of Psychology, Institute for ClinicalPsychology and Psychotherapy, Medical School Hamburg, Hamburg, Germany.
5First Department of Medicine, University Medical Centre Hamburg-Eppen‑
dorf (UKE), Hamburg, Germany. 6 Medicover Neuroendocrinology, Munich,Germany. 7 Institute for Sex Research, Sexual Medicine and Forensic Psychiatry,
University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 8 Depart‑
ment of Gynecology and Obstetrics, CCC Erlangen EMN, Friedrich Alexander
University, Erlangen, Germany. 9 Department of Psychiatry and Psychotherapy,
Social and Emotional Neuroscience Group, Center for Psychosocial Medi‑cine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
10
Division of Pediatric Endocrinology and Diabetes, Department of Children
and Adolescent Medicine I, University Hospital of Schleswig-Holstein, Campus
Kiel/Christian-Albrechts University of Kiel, Kiel D‑24105, Germany. 11 Instituteof Clinical Molecular Biology, Christian-Albrechts-University Kiel, University
Hospital Schleswig-Holstein, Rosalind‑Franklin‑Str. 12, Kiel 24105, Germany.
12
Hamburg Centre for Translational Immunology (HCTI), University Medi‑
cal Centre Hamburg-Eppendorf, Hamburg, Germany. 13 Martin Zeitz Center
for Rare Diseases, University Medical Center Hamburg-Eppendorf, Hamburg,
Germany.

3.
4.
5.
6.
7.
8.
9.
10.
11.
12.

13.
14.
15.
16.
17.
18.

19.
20.

21.
22.

Received: 5 April 2024 Accepted: 29 July 2024
23.

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