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A genetic link between gender dysphoria and sex hormone signalling

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Abstract

Context There is a likely genetic component to gender dysphoria, but association study data have been equivocal. Objective We explored the specific hypothesis that gender dysphoria in transwomen is associated with variants in sex hormone signalling genes responsible for undermasculinization and/or feminization. Design Subject-control analysis included 380 transwomen and 344 control males. Associations and interactions were investigated between functional variants in 12 sex hormone signalling genes and gender dysphoria in transwomen. Setting Patients were recruited from the Monash Gender Clinic, Monash Health, Melbourne, Australia and the University of California, Los Angeles. Patients Caucasian transwomen, pre- and post-operative diagnosed with transsexualism (DSM-IV) or gender dysphoria (DSM-V) were recruited. Most were receiving hormone treatment at the time of recruitment. Main Outcome Measured Genomic DNA was genotyped for repeat length polymorphisms or SNPs. Results A significant association was identified between gender dysphoria and ERα, SRD5A2 and STS alleles, as well as ERα and SULT2A1 genotypes. Several allele combinations were also over-represented in transwomen, most involving AR (AR-ERβ, AR-PGR, AR-COMT, CYP17-SRD5A2). Over-represented alleles and genotypes are proposed to undermasculinize/feminise based on their reported effects in other disease contexts. Conclusions Gender dysphoria may have an oligogenic component with several genes involved in sex hormone signalling contributing.
A genetic link between gender dysphoria and sex hormone signalling
Madeleine Foreman, Lauren Hare, Kate York, Kara Balakrishnan, Francisco J. Sánchez,
Fintan Harte, Jaco Erasmus, Eric Vilain and Vincent R. Harley
The Journal of Clinical Endocrinology & Metabolism
Endocrine Society
Submitted: May 22, 2018
Accepted: September 18, 2018
First Online: September 21, 2018
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Gender dysphoria and sex hormone signaling
A genetic link between gender dysphoria and sex hormone signalling
Madeleine Foreman
1
, Lauren Hare
1
, Kate York
1
, Kara Balakrishnan
1
, Francisco J. Sánchez
3
,
Fintan Harte
2
, Jaco Erasmus
2
, Eric Vilain
4
and Vincent R. Harley
1
1
Hudson Institute of Research, Melbourne, Australia;
2
Monash Gender Clinic, Monash Health, Melbourne,
Australia;
3
University of Missouri, Columbia, MO, USA;
4
Children’s National Health System, Washington, DC,
USA
ORCiD numbers:
0000-0002-2405-1262
Harley
Vincent
Received 22 May 2018. Accepted 18 September 2018.
Context — There is a likely genetic component to gender dysphoria, but association study
data have been equivocal.
Objective — We explored the specific hypothesis that gender dysphoria in transwomen is
associated with variants in sex hormone signalling genes responsible for
undermasculinization and/or feminization.
Design — Subject-control analysis included 380 transwomen and 344 control males.
Associations and interactions were investigated between functional variants in 12 sex
hormone signalling genes and gender dysphoria in transwomen.
Setting — Patients were recruited from the Monash Gender Clinic, Monash Health,
Melbourne, Australia and the University of California, Los Angeles.
Patients — Caucasian transwomen, pre- and post-operative diagnosed with transsexualism
(DSM-IV) or gender dysphoria (DSM-V) were recruited. Most were receiving hormone
treatment at the time of recruitment.
Main Outcome Measured — Genomic DNA was genotyped for repeat length
polymorphisms or SNPs.
Results — A significant association was identified between gender dysphoria and ER
α
,
SRD5A2 and STS alleles, as well as ERα and SULT2A1 genotypes. Several allele
combinations were also over-represented in transwomen, most involving AR (AR-ER
β
, AR-
PGR, AR-COMT, CYP17-SRD5A2). Over-represented alleles and genotypes are proposed to
undermasculinize/feminise based on their reported effects in other disease contexts.
Conclusions—Gender dysphoria may have an oligogenic component with several genes
involved in sex hormone signalling contributing.
In this study we identified a genetic association between gender dysphoria in transwomen and
polymorphisms in genes involved in sex hormone signalling. .
Introduction
Gender identity—our sense of being male or female—develops early in life. By age 2, most
children are able to identify their own gender, which is typically consistent with the sex they
were at birth (1, 2). Yet, a small percentage of people will report significant clinical distress
because their sex at birth does not reflect their gender identity (3). In extreme cases, patients
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will be given the diagnosis of gender dysphoria and may undergo medical treatments to
better align their anatomy and physiology with their gender identity.
Many identity labels may be used among this group of people, with transgender being a
broad, encompassing term for many subtypes. In this report, we focus on transwomen, or
people male at birth and who later transitioned to be female (historically referred to as male-
to-female transsexual). Unlike other people who may be transgender, transwomen take steps
to affirm their gender identity by social and/or physical transitioning from their birth sex to
their experienced gender through cross-hormone treatment and surgery (4).
The aetiology of gender dysphoria is unknown, yet the reported prevalence has been
increasing with most estimates suggesting that as many as 521 in 100,000 males and 265 in
100,000 females experience gender dysphoria (5). Early research into gender dysphoria
focused on the belief that it was a psychological condition and suggested that dysfunctional
family dynamics (6) and traumatic childhood experiences (7) may contribute. However,
recent studies point towards a biological basis involving endocrine, neurobiological and
genetic factors. For instance, an increased prevalence of gender dysphoria was observed
amongst people who experienced atypical prenatal androgen exposure in utero, such as
females with Congenital Adrenal Hyperplasia (8-15). Neuroimaging studies revealed specific
regions in the brains of transwomen that may be more similar to the brains of control women
than that of control men (16,17,18). Heritability studies suggest a genetic component, as 23-
33% of monozygotic twin pairs are concordant for gender dysphoria (19).
Candidate gene association studies have begun to investigate whether functional variants
in sex hormone signalling genes are associated gender dysphoria. It is proposed that
functional variants may alter sex hormone signalling, causing atypical sexual differentiation
of the developing brains for those who will later experience gender dysphoria (20). Some
associations have been identified, including an over-representation of long CAG repeats in
the AR of transwomen (21) and an over-representation of the CYP17 T/C SNP (22, 23), ERβ
CA repeat (24) and ERα Xbal A/G SNP (25) in transgender men. Other studies found no
associations (26-28). Most studies have been limited by small sample sizes and there is a
need to reproduce findings in large, independent cohorts.
We hypothesise that gender dysphoria in transwomen is associated with genetic variants
in sex hormone signalling genes responsible for undermasculinization and/or feminization of
the brain. The aim is to conduct a genetic association study of twelve sex signalling genes
including COMT, CYP11A1, HSD17B6, STS and SULT2A1, which have not previously been
studied in the context of gender dysphoria. Here we determine the allele and genotype
frequencies of variable polymorphic lengths of seven genes and single nucleotide
polymorphisms of five genes in Caucasian transwomen and compared these with Caucasian
male control subjects.
Methods and Materials
Participants
Three hundred and eighty Caucasian transwomen, pre- and post-operative diagnosed with
transsexualism (DSM-IV) or gender dysphoria (DSM-V) were recruited from the Monash
Medical Centre (MMC), Victoria, Australia (n = 222) and the University of California, Los
Angeles (UCLA) (n = 158). Most were receiving hormone treatment at the time of
recruitment. Three hundred and forty-four Caucasian male control subjects without gender
dysphoria were also recruited from Monash Medical Centre (n = 281) and UCLA (n = 63).
All transwomen and non-transgender male controls were determined to be Caucasian, based
upon their surname if ethnicity was not specified (29). Subjects who identified themselves as
non-caucasian were excluded. Ethics approval for this study were obtained from Monash
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Medical Centre and UCLA, and consent procedures adhered to the tenets of the Declaration
of Helsinki.
Genotyping
Genomic DNA was extracted from whole blood (30) or saliva (Oragene
TM
) samples.
Androgen receptor (AR) exon 1 CAG repeat, estrogen receptor α (ERα)
promoter region TA
repeat, estrogen receptor β (ERβ) intron 5 CA repeat cytochrome P450 family 11 subfamily A
member 1 (Cyp11a1) promoter region TTTTTA repeat, aromatase (Cyp19) intron 5 TTTA
repeat and progesterone receptor CA repeat fragment lengths were amplified by polymerase
chain reaction (PCR) and sized by automated capillary electrophoresis (21). Steroid 5-
α reductase 2 3’untranslated region (UTR) TA repeat was genotyped by PCR directly
followed by gel electrophoresis (31). Single nucleotide polymorphisms (SNP) in catechol-O-
methyltransferase (exon 3 G/A SNP), cytochrome P450 17α-hydroxylase/17,20-lyase
(5’UTR T/C SNP), 17β hydroxysteroid dehydrogenase 6 (intron 1 T/C SNP), steroid
sulfatase (intron 2 A/G SNP) and sulfotransferase (3’UTR T/C SNP) were determined by
agarose gel electrophoresis, following PCR and restriction enzyme digestion (31-34).
Oligonucleotide pairs, restriction enzymes and optimal annealing temperatures used are
shown in Supplementary Table 1. Genotyping data was removed if the subject was
determined to be non-Caucasian or have a DSD post-genotyping or if a sample had a
genotype failure rate greater than 20%, the removed samples are shown in Supplementary
Table 2. Each gene was successfully genotyped, with n numbers ranging from 320 – 343
transwomen and 259 – 283 non-transgender male controls (> 90% of the sample cohort).
Statistics
To evaluate the repeat length polymorphism data for possible associations with transwomen,
the distribution of repeat lengths of AR, ERα, ERβ, CYP11A1, CYP19 and PGR were
analysed using the non-parametric Mann-Whitney U test. Repeat lengths were divided into
short or long alleles based upon the median repeat length of the male control group. Allele
and genotype frequencies of all twelve genes (stratified repeat length polymorphisms and
SNPs) were compared using the chi-square test for independence. Binary logistic regression
was used to measure of the strength of the associations with gender dysphoria and evaluate
possible interactions between the twelve genes. Analyses were performed using SPSS 23.0. A
p value < .05 was considered significant.
Results
Polymorphic fragments lengths were obtained for 320-343 transwomen and 269-283 male
controls. The number of repeats identified for each allele is shown in Supplementary Table 3.
Median values were calculated from 24 repeat length distributions. A difference in median
repeat length was identified, with transwomen having a significantly shorter median repeat
length (16 TA repeats) for ERα when compared to male controls (17 TA repeats) (p = 0.03)
(Table 1).
Allele frequencies were determined for the five SNPs (COMT, CYP17, HSD17B6,
SULT2A1 and STS) and the dichotomous SRD5A2 repeat length polymorphism (Table 2). A
difference between transwomen and male control allele frequencies was identified in two of
the six genes. Specifically, in transwomen compared to male controls, there was an over-
representation of both the TA(9) repeat in SRD5A2 (12.3% compared to 8.5%, p = 0.030) and
the G allele in STS (91.2% compared to 85.9%, p = 0.015).
To compare genotypes repeat lengths were assigned to “short” or “long” allele groups
based upon the median repeat length of the control population for the six repeat length
polymorphism genes (AR short 22, long >22; CYP11A1 short 4, long >4; CYP19 short 7,
long >7; ERα short 17, long >17; ERβ short 23, long >23; PGR short 18, long >18). The
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genotypes of CYP11A1, CYP19, ERα, ERβ and PGR polymorphisms for all individuals were
determined as SS (two short alleles), SL (one short and one long allele) or LL (two long
alleles). As the AR gene is located on the X chromosome it is hemizygous and the allele and
genotype frequencies are equivalent.
Genotype frequencies of the stratified repeat length polymorphisms (in CYP11A1,
CYP19, ERα, ERβ, PGR, SRD5A2) and of the SNPs (in COMT, CYP17, HSD17B6, STS,
SULT2A1) were analysed using binary logistic regression. An association was identified
between transwomen and the SULT2A1 homozygous TC genotype (p = 0.009) and the ERα
SS genotype (p = 0.035) when compared to male controls (Table 3). The odds ratios indicate
that within this population, the likelihood of being transgender increases by 1.61 times (95%
CI 1.13-2.31) if an individual possesses the SULT2A1 TC genotype and increases by 1.65
times (95% CI 1.04 - 2.63) if an individual possesses the ERα SS genotype.
Of possible two-locus gene interactions modelled using binary logistic regression, four
interactions were over-represented in transwomen when compared to male controls: AR-
ERβ, AR-PGR, AR-COMT, CYP17-SRD5A2 (Table 4). Notably, three of the four interactions
involve the long CAG repeats of the AR.
Discussion
To date, this is the largest study of gender dysphoria conducted, examining 12 genes.
Variants within COMT, CYP11A1, HSD17B6, STS and SULT2A1 have not previously been
studied in transgender men or women. In addition, this is the first of three studies to identify
an association between TA repeats in ERα and gender dysphoria. This study did not
reproduce the independent associations between ERβ and gender dysphoria in transwomen
reported by Henningson et al. (35) or the association with long CAG repeats in AR,
previously identified in a subset of this cohort (21). However, both ERβ and AR were
identified to be overrepresented in transwomen when in combination with other genes,
supporting their involvement in the development of gender dysphoria.
Associations were identified between genetic variants in ERα, SRD5A2, STS and
SULT2A1 and this cohort of transwomen. These genetic variants are suspected to be
functional which permits us to examine the predicted functional effects of the specific
polymorphism over-represented in transwomen. In ERα, for example, short TA repeats
overrepresented in transwomen are also associated with low bone mineral density in women
(36). Therefore, we speculate that estrogen signalling, is reduced (37). In SULT2A1, the
heterozygous TC genotype is overrepresented in transwomen. The minor, C allele of
SULT2A1 is associated with elevated sex hormone-binding globulin (38), a glycoprotein that
regulates circulatory sex steroid bioavailability and is present within fetal male blood during
early gestation (39). In transwomen with the TC SNP, we speculate that fetal sex hormone
binding globulin levels are increased which may reduce the effects of circulating hormones.
Polymorphisms in two genes were over-represented in transwomen by allele analysis but not
by the (more stringent) genotype analysis. First, TA(9) of SRD5A2 is associated with reduced
prostate cancer risk likely due to reduced DHT (40), suggesting that levels of the potent
androgen DHT could be reduced among transwomen. Second, the G allele in STS is
associated with reduced enzyme levels, mostly among studies of ADHD (41), a condition
with 5-fold increased incidence of gender dysphoria (42), suggesting a possible overlap in
aetiology.
Four significant two-locus interactions were identified by binary logistic regression
modelling; AR-ERβ, AR-PGR, AR-COMT and CYP17-SRD5A2. Of these, three involved long
CAG repeats of the AR. While long CAG repeats in AR alone may not have an independent
effect on the development of gender dysphoria, this AR polymorphism may interact with
other genes to increase the likelihood of being transgender. This is consistent with a previous
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finding by Hare et al. (21) who identified an increased proportion of long AR repeat lengths
within a subset of the population of transwomen in this study. Long CAG repeats reduce AR
signalling (43-45). Similarly, long repeats in ERβ have been associated with decreased ERβ
signalling (36), potentially reducing the influence of ERβ on the defeminization of the male
brain (46). In combination, both genotypes appear to have additive effects on the
development of gender dysphoria. In contrast, the interaction of AR and COMT is unclear
where the Met
158
homozygous genotype is known to reduce COMT activity (47), affecting
estrogen catechol metabolism. Also, the functional effect of the PGR polymorphism is
unclear in transwomen. Interaction analysis also identified the specific combination of
SRD5A2 and CYP17 polymorphism, the former associated with reduced levels of DHT (48)
while the latter is known to increase sex steroid precursor production (49). It seems plausible
that together, these polymorphisms may increase the production of precursor steroids and
testosterone, but not of DHT, the more potent androgen form.
A limitation of the study is that patients and controls were obtained from 2 sites, in
Australia and the USA, and therefore likely to represent genetically different populations.
Another limitation of this study is the use of Caucasian surnames as a selection criteria.
Future and more detailed genetic analyses such as GWAS, would give insight into the
ethnicity of the cohort, obviating the need for selection criteria based upon ethnicity.
In summary, our study of transwomen supports the hypothesis that gender dysphoria has
a polygenic basis, involving interactions between multiple genes and polymorphisms that
may alter the sexual differentiation of the brain in utero, contributing to the development of
gender dysphoria in transwomen. However, while discordance rates for gender dysphoria
suggest that genetics plays a role, it is not the sole determinant of gender identity. GWAS,
genome and methylome approaches especially when coupled with neuroimaging or sex
steroid measurements should be undertaken to allow a better understanding of how genetic
variants contribute to gender dysphoria.
Transgender people continue to be subjected to high rates of gender-based discrimination
when seeking medical care, employment and education (50, 51). Although people’s civil
rights should not hinge on science to validate their individuality and lived experience,
determining what biological factors contribute to gender dysphoria may influence public
opinion and public policies related to the transgender community. More importantly, such
knowledge can be used to improve diagnosis and treatment for transgender people (e.g.,
differentiating which children with gender dysphoria will persist into adulthood versus
remit). Therefore, there is a clinical need to investigate further the genetic and biological
basis of gender dysphoria.
Acknowledgements
This work was supported by the National Health and Medical Research Council (NHMRC,
Australia) Program Grant 1074258 (to V.R.H.) and the Victorian Government’s Operational
Infrastructure Support Program. V.R.H. is the recipient of the NHMRC (Australia) Research
Fellowship 441102. We also thank the individuals who voluntarily participated and who are
an integral part of this research. The authors have no conflicts of interest to declare.
FUNDING: This work was supported by the National Health and Medical Research Council
(NHMRC, Australia) Program Grant 1074258 (to V.R.H.) and the Victorian Government’s
Operational Infrastructure Support Program. V.R.H. is the recipient of the NHMRC
(Australia) Research Fellowship 441102.
National Health and Medical Research Council
http://dx.doi.org/10.13039/501100000925, 1074258, Vincent Harley; National Health
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and Medical Research Council http://dx.doi.org/10.13039/501100000925, 441102,
Vincent Harley
Corresponding Author: Vincent Harley, Hudson Instiutte of Medical Research,
Vincent.harley@hudson.org.au, +61 3 8572 2527
DISCLOSURE STATEMENT:
The authors have nothing to disclose.
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Table 1 Comparison of repeat length distributions of AR, ERα, ERβ, CYP11A1, CYP19 and
PGR repeat length polymorphisms
Gene
Male Control
Transgender Women
Mann
Whitney U Test p
value
n
Median
n
Median
AR 289 22 327 22 0.31
ERα 567 17 640 16 0.03*
ERβ 580 23 668 23 0.70
CYP11A1 546 4 668 4 0.55
CYP19 580 7 658 7 0.21
PGR 562 18 676 18 0.20
* denotes a significant p-value < 0.05.
Table 2 Allele frequencies of the COMT, CYP17, HSD17B6, SRD5A2, STS and SULT2A1
single nucleotide or dichotomous polymorphisms
Gene Allele Male Controls Transgender women P-value
n
%
n
%
COMT G 303 58.7 356 54.1 0.11
A 213 41.3 302 45.9
CYP17 T 354 63.7 384 58.9 0.090
C 202 36.3 268 41.1
HSD17B6 T 366 65.6 406 60.2 0.053
C 192 34.3 268 39.8
SRD5A2 TA(0) 516 91.5 598 87.7 0.030*
TA(9) 48 8.5 84 12.3
STS G 238 85.9 302 92.1 0.015*
A 39 14.1 26 7.9
SULT2A1 T 419 80.9 504 77.5 0.16
C 99 19.1 146 22.5
The p-value was calculated using the chi-square test. *denotes the p-value is significant (<0.05).
Table 3 Genotype analysis of the COMT, CYP11A1, CYP17, CYP19, ERα, ERβ, HSD17B6,
PGR, SRD5A2 and SULT2A1 polymorphisms
Gene
Genotype
Male Control
Transgender Women
P
value
OR, 95% CI)
n
%
n
%
COMT GG 85 32.8 100 30.4 0.06 (1.59, 0.98 - 2.58)
GA 135 52.1 156 47.4
AA 39 15.1 73 22.2
CYP11A1 SS 89 33.1 124 37.1 0.24 (0.81, 0.57 - 1.15)
SL 138 51.3 155 46.4
LL 42 15.6 55 16.5
CYP17 TT 112 40.3 109 33.2 0.097 (1.34, 0.95 - 1.91)
TT 130 46.8 170 51.8
CC 36 12.9 85 14.9
CYP19 SS 86 30.3 83 25.2 0.20 (1.36, 0.85 - 2.16)
SL 142 50.2 174 52.9
LL 55 19.4 72 21.9
ERα SS 75 27 103 32.2 0.035* (1.65, 1.04 - 2.63)
SL 138 49.6 163 50.9
LL 65 23.4 54 16.9
ERβ SS 186 65.7 216 64.7 0.81 (1.04, 0.74 - 1.45)
SL 85 30 103 30.8
LL 12 4.2 15 4.5
HSD17B6 TT 122 43.7 123 36.5 0.091 (1.53, 0.93 - 2.51)
TC 122 43.7 160 47.5
CC 35 12.5 54 16
PGR SS 81 29.3 106 31.4 0.35 (0.80, 0.50 - 1.27)
SL 135 48.9 169 50
LL 60 21.7 63 18.6
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SRD5A2 TA(0)/(0) 238 84.4 269 78.4 0.12 (1.42 0.92 - 2.18)
TA(0)/(9) 40 14.2 64 18.7
TA(9)/(9) 4 1.4 10 2.9
SULT2A1 TT 175 67.6 192 58.9 0.009* (1.61, 1.13 - 2.31)
TC 69 26.6 122 37.4
CC 15 5.8 12 3.7
S = short alleles L = long alleles. P-values, odds ratios (OR) and 95% confidence intervals (CI) were calculated
using binary logistic regression. ORs greater than 1 indicate an increased likelihood of being transgender
compared to the reference allele. ORs less than one indicate a decreased likelihood of being transgender
compared to the reference allele. *denotes statistical significance (p<0.05).
Table 4 Odd’ ratios and 95% confidence intervals of significant two-locus gene interactions
determined by binary logistic regression modelling.
Two
locus gene interactions
OR
95% CI
P
value
Lower
Upper
AR (L) – ERβ (SL) 2.78 1.15 6.70 0.023
AR (L) – PGR (LL) 5.68 1.63 17.95 0.006
AR (L) – COMT (AA) 3.88 1.2 12.56 0.024
CYP17 (A1A2) – SRD5A2(TA(0)/TA(9)) 4.09 1.19 14.03 0.025
The interacting genotypes for each gene are shown in brackets. Fragment length alleles polymorphisms were
analysed as dichotomous short (S) or long (L) variables. The odds ratio (OR), 95% confidence interval (CI) and
p-value were computed using binary logistic regression. n = 233 transgender women and 195 male controls.
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... The authors identified a unique link between TA repeats in ERα and gender dysphoria. While some previously reported associations were not replicated, interactions between genes like AR, ERβ, and others were highlighted (20). ...
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... This statement highlights the uncertainty and lack of fact in cause of sexual identity and related disorders. "The etiology of gender dysphoria is unknown, yet the reported prevalence has been increasing, with most estimates suggesting that as many as 521 in 100,000 males and 265 in 100,000 females experience gender dysphoria" (Foreman et al., 2019). The reported prevalence may be increasing due to the warming of social acceptance. ...
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