Abstract
Introduction
Brain sexual differentiation results from the effects of sex steroids on the developing brain. The presumptive route for brain masculinization is the direct induction of gene expression via activation of the estrogen receptors α and β and the androgen receptor through their binding to ligands and to coactivators, regulating the transcription of multiple genes in a cascade effect.
Aim
To analyze the implication of the estrogen receptor coactivators SRC-1, SRC-2, and SRC-3 in the genetic basis of gender incongruence.
Main Outcome Measures
Analysis of 157 polymorphisms located at the estrogen receptor coactivators SRC-1, SRC-2, and SRC-3, in 94 transgender versus 94 cisgender individuals.
Method
Using SNPStats software, the allele and genotype frequencies were analyzed by χ2, the strength of the association was measured by binary logistic regression, estimating the odds ratio for each genotype. Measurements of linkage disequilibrium and haplotype frequencies were also performed.
Results
We found significant differences at level P < .05 in 8 polymorphisms that correspond to 5.09% of the total. Three were located in SRC-1 and 5 in SRC-2. The odds ratio analysis showed significant differences at level P < .05 for multiple patterns of inheritance. The polymorphisms analyzed were in linkage disequilibrium. The SRC-1 haplotypes CGA and CGG (global haplotype association P < .009) and the SRC-2 haplotypes GGTAA and GGTAG (global haplotype association P < .005) were overrepresented in the transgender population.
Conclusion
The coactivators SRC-1 and SRC-2 could be considered as candidates for increasing the list of potential genes for gender incongruence. Ramírez KDV, Fernández R, Delgado-Zayas E, et al. Implications of the Estrogen Receptor Coactivators SRC1 and SRC2 in the Biological Basis of Gender Incongruence. Sex Med 2021;9:100368.
Key Words: Estrogens, Estrogen Coactivators, Gender Dysphoria, Gender Incongruence, SRC-1, SRC-2, SRC-3
INTRODUCTION
The term gender identity refers to a person's innermost sense of their own gender,1,2 while sex refers to the biological sex characteristics, based on chromosomal, hormonal, physical, and anatomical characteristics. For clarity in this work, sex will be used interchangeably with natal sex, biological sex, and sex assigned at birth.
Gender identities are classified into “cisgender” and “transgender” umbrellas. Cisgender is used to refer to a gender identity that matches a person's natal sex, while transgender refers to a gender identity that differs from the sex assigned at birth. Gender Incongruence (GI) in the International Classification of Diseases ICD-113 and Gender Dysphoria (GD) in the Diagnostic and Statistical Manual of Mental Disorders DSM-54 are characterized by a marked incongruence between one's experienced gender and the sex assigned at birth. In order to meet criteria for the diagnosis of GD, the condition must also be associated with clinically significant distress or impairment in social, occupational, or other important areas of functioning.3
The origin of GI3 appears to be multifactorial. It might be associated with neurodevelopmental processes of the brain5,6 under the influence of testosterone converted into estradiol in the brain by the action of the aromatase, during a critical period of development. Thus, in mammals, sex differences in the adult brain are established very early in development, when the brain is very immature.7 In the case of having inherited the SRY gene, during embryogenesis, testosterone secreted by the testes enters the brain and is converted to estradiol by the aromatase.8 Then, the estradiol acts in the brain by binding to intracellular estrogen receptors located predominantly in neurons, masculinizing specific brain regions.
But a genetic component may also be involved in GI since siblings of transgender individuals are more likely to be transgender, compared with the general population.9 Most genetic studies that investigate the genetic component of gender incongruence analyze the implication of polymorphisms related to the estrogen receptors (ERs) α and β, the androgen receptor AR or the aromatase CYP19A1,10, 11, 12, 13, 14, 15, 16, 17 as well as the interaction effects (epistasis) between them18 or the effect of epigenetics.19,20 This gene selection is based on the fact that sex hormone receptors belong to the nuclear receptor superfamily of ligand activated transcriptional factors. In the case of the AR, their ligand is androgen21 while for the ER is estrogen, 17β-Estradiol (E2) in particular.22 E2 exerts a wide variety of effects on growth, development, the function of reproductive systems and regulation in the central nervous system.22,23 The mechanism of action of the two isoforms ERα and ERβ consists of binding with the E2 ligand to obtain the receptor`s dimerization (Figure 1), originating the necessary conformational changes in the ligand binding domain (LBD)24 and coupling with the estrogen response elements (EREs)24 in the genes that are regulated by E2. On the other hand, this conformational change in the LBD allows coactivators and other coregulating proteins to be recruited. This step is critical for the transcriptional regulation of genes induced by E225 (Figure 1).
Figure 1.
Molecular mechanisms of action of ERs. Hormone 17β-Estradiol (E2) binds to the nuclear receptor (ERα or ERβ), and after dimerization and translocation to the nucleus, the nuclear receptor complex binds to a specific sequence of DNA known as an estrogen response element (ERE). The nuclear receptor DNA complex in turn recruits the SRCs coactivators that activate the transcription of gene targets.
Among the coactivating proteins are the steroid receptor coactivators (SRCs)26 that consist of three related members: SRC-1, SRC-2, and SRC-3. The role of SRCs in ER-mediated gene expression was demonstrated by the discovery of increased amplification of the AIB1 gene in ER-positive breast and ovarian cancer cells27 and partial resistance to E228,29 is evident in knock-out mice SRC-1.
Estrogen is produced in many regions of the brain including the hippocampus, the cortex, the cerebellum, the hypothalamus, and the amygdala.30 The actions of estradiol in the developing brain are generally permanent and range from the establishment of sexual differences (cerebral dimorphism), to generalized trophic and neuroprotective effects.31
Given the importance of estrogens in brain dimorphism, and the critical role of the coactivators in the transcriptional regulation of genes induced by E2, and based on previous genetic studies,10, 11, 12, 13, 14, 15, 16, 17 in the present research we analyzed 157 polymorphisms located at SRC-1, SRC-2 and SRC-3 coactivators in a transgender versus a cisgender population. We postulated that variation at the DNA level at the steroid receptor coactivators (SRC-1, SRC-2, and/or SRC-3) could affect the function of the E2-ER complex, and consequently could also modify the transcription of the genes regulated by E2.
METHODS AND MATERIALS
Participants
We analyzed 94 transgender individuals (47 transmen and 47 transwomen) versus 94 cis gender individuals (44 cismen and 50 ciswomen). The transgender population was recruited and diagnosed through the Gender Unit of the Clínic Hospital of Barcelona (Spain) at the moment of starting gender-affirming hormonal treatment. All transgender participants identified with the other gender (male or female) and were erotically attracted to persons with the same anatomical sex. All of them presented an early onset of gender nonconformity, before or at puberty, and showed a marked intensity of gender dysphoria. Sexual orientation was established by asking which partner (a man, a woman, both or neither) they would prefer or feel attraction to if they were completely free to choose and their body did not interfere.
The inclusion criteria were: presenting gender incongruence according to ICD-113 and having no disorder of sexual development. The exclusion criteria for all participants were DSD (differences in sex development), neurological and hormonal disorder, major medical condition and history of alcohol and/or drug abuse. To rule out the presence of psychiatric disorders and substance abuse in all participants, the Mini-International Neuropsychiatric Interview32 was administered.
The cisgender population was selected from a country census (Pizarra, Málaga, Spain) matched by geographic origin, race, and sex. The main characteristics of the Pizarra census were described in a previous study.33
Written informed consent was obtained from the transgender group after full explanation of the procedures. The DNA samples of the cisgender group were recruited from the biobank generated for the Pizarra study, in which all participants signed informed consent for donation of the samples to the biobank of the Hospital Regional Universitario de Málaga for medical research studies. The study was approved by the UNED Ethics Committee.
DNA Analysis
Genomic DNA was extracted from EDTA blood samples using the DNeasy Blood & Tissue Kit from Qiagen (Madrid, Spain) according to the manufacturer's protocol. The analyzed polymorphisms were single nucleotide polymorphisms (SNPs) located, according to the Ensembl database (www.ensembl.org/), in the steroid receptor coactivators SRC-1, SRC-2, and SRC-3. Genotyping was performed by the array Axiom Spanish BioBank (Affymetrix). Statistical analyses were performed using the free online software SNPStats (http://bioinfo.iconcologia.net/SNPstats).
Statistical Analyses
The analyses were conducted by chromosomic sex, in 2 independent populations: individuals assigned as females at birth and individuals assigned as males at birth, considering significant a P value lower than .05.
The allele and genotype frequencies were analyzed by χ2 test. The strength of the associations with gender incongruence was measured by binary logistic regression, estimating the odds ratio (OR) for each genotype.
Polymorphisms located very close to each other in the same chromosome tend to be inherited together with a high degree of correlation. This correlation, called linkage disequilibrium, was also analyzed. Moreover, we were also interested in the simultaneous analysis of multiple loci (haplotypes), given that they may themselves be causal variants.34
Measurement of linkage disequilibrium, designated as D' and r2, and subsequent measurement of haplotype frequencies were performed using the free online software SNPStats (http://bioinfo.iconcologia.net/SNPstats)35 using logistic regression models to determine the strength of the associations. In all analyses, a missing value for any response, polymorphism, or covariate was cause for exclusion of that individual from the analysis. Any false positives were controlled with the Bonferroni correction (P < .05/157 = .0003). A post-hoc power analysis showed a 67.8% power, with the following study parameters: incidence group (1) 45.74%, incidence group (2) 28.72%. Subjects, group (1): 94. Subjects group (2): 94. Alpha = 0.05.
RESULTS
Analysis of Allele and Genotype Frequencies
We analyzed 157 SNPs distributed in the coactivators SRC-1 (63 SNPs), SRC-2 (64 SNPs), and SRC-3 (30 SNPs) (Table 1) in 94 transgender individuals (47 transmen and 47 transwomen) versus 94 cis gender individuals (44 cismen and 50 ciswomen). All the polymorphisms were in Hardy-Weinberg equilibrium. The prevalence rates for all analyzed polymorphisms were similar to those found in the global 1000 genomes and the European 1000 genomes http://www.1000genomes.org.
Table 1.
Description of the analyzed SRCs
| Gene | Chromosome | Location | Function | Analyzed SNPs | SNPs with significant differences |
|---|---|---|---|---|---|
| SRC-1 | 2 | 24491254-24770702 | The protein encoded by this gene acts as a transcriptional coactivator for steroid and nuclear hormone receptors. | 63 | 3 |
| SRC-2 | 8 | 70109770-70405390 | The encoded protein acts as an intermediary factor for the ligand-dependent activity of nuclear receptors, which regulate their target genes upon binding of cognate response elements. | 64 | 5 |
| SRC-3 | 20 | 47501887-47656872 | The protein encoded by this gene is a nuclear receptor coactivator that interacts with nuclear hormone receptors to enhance their transcriptional activator functions | 30 | 0 |
| Total SNPs | 157 | 8 | |||
| % | 100 | 5.09 |
This table shows the main characteristic of the SRCs analyzed: the gene name, the chromosome location, the main function of the protein, the number of SNPs analyzed and the number of the polymorphisms (SNPs) that showed statistical significance P < .05.
When we compared the distribution of the allele frequencies, we found significant differences in 8 SNPs that correspond to 5.09% of the analyzed polymorphisms: three located in SRC-1 (polymorphisms 1, 2, and 3) and five in SRC-2 (polymorphisms 4 to 8) (Table 1). The description of the statistically significant polymorphisms is in Tables 1 and 2.
Table 2.
Description of the SNPs with significant differences
| Gene | Polymorphism | Alias | DNA variation | Regulation by Ensembly | Our study frequency | Global 1000 genomes frequency | European 1000 genomes frequency |
|---|---|---|---|---|---|---|---|
| SRC-1 | rs10495747 | P1 | T/C | Intron Variant | C= 0.11 | C=0.1330 | C=0.1153 |
| rs2584940 | P2 | T/G | Regulatory Region Variant/ Intron Variant |
G= 0.38 | G=0.4605 | G=0.4125 | |
| rs6756785 | P3 | A/G | Intergenic Variant/ 500B Downstream Variant | G=0.32 | G=0.2115 | G=0.2883 | |
| SRC-2 | rs76968380 | P4 | G/A | Intergenic Variant | A=0.06 | A=0.1138 | A=0.0646 |
| rs34406737 | P5 | G/A | Intergenic Variant | A=0.15 | A=0.1300 | A=0.1262 | |
| rs1963250 | P6 | G/T | Intergenic Variant | T=0.57 | T=0.5691 | T=0.5368 | |
| rs10755950 | P7 | G/A | Intergenic Variant | A=0.42 | A=0.5655 | A=0.4483 | |
| rs56055423 | P8 | A/G | Intergenic Variant | G=0.05 | G=0.0132 | G=0.0457 |
This table shows the main characteristic of the polymorphisms that showed statistical significance: the gene name, the polymorphism name, the alias used in this work, the DNA variation, the gene location of the polymorphisms, and the frequencies of the polymorphisms in our study versus the Global 1000 genomes and the European 1000 genomes databases.
Association Analysis of Each Polymorphism With Gender Incongruence
We found significant differences in the analysis of the strength of the association with gender incongruence. The odds ratio (OR) analysis for the P1 to P8 polymorphisms showed significant differences for multiple patterns of inheritance (Table 3):
P1 polymorphism: The genotype T/T was overrepresented in the cis population (OR > 2.13; P < .034 for the dominant model).
P2 polymorphism: The genotype T/T was overrepresented in the cis population (OR > 2.12; P < .014).
P3 polymorphism: The genotype A/A was overrepresented in the cis population (OR > 2.19; P < .008 for the dominant model).
P4 polymorphism: The genotype G/G was overrepresented in the cis population (OR > 2.58; P < .033 for the log-additive model).
P5 polymorphism: The G/G genotype was overrepresented in the trans population while the A/G genotype was overrepresented in the cis population (OR > 0.48; P < .003 for the codominant model).
P6 polymorphism: The T/T genotype was overrepresented in the trans population while the T/G and G/G were overrepresented in the cis population (OR > 0.42; P < .007 for the dominant model).
P7 polymorphism: The A/A genotype was overrepresented in the trans population (OR > 2.42; P < .024 recessive model).
P8 polymorphism: The genotype A/A was overrepresented in the cis population (OR > 4.83; P < .007 dominant model; OR > 4.64; P < .006 log-additive model).
Table 3.
Polymorphism association analysis with gender incongruence, in different models of inheritance (n = 188, crude analysis)
| Model | Genotype | Cis groups (%) | Trans groups (%) | OR | P | AIC | BIC |
|---|---|---|---|---|---|---|---|
| P1 polymorphism (rs10495747) | |||||||
| Codominant | T/T | 79 (84%) | 67 (71.3%) | 1.00 (reference) | .07 | 263.1 | 276 |
| T/C | 15 (16%) | 26 (27.7%) | 2.05 (1.00–4.19) | ||||
| C/C | 0 (0%) | 1 (1.1%) | NA (0.00–NA) | ||||
| Dominant | T/T | 79 (84%) | 67 (71.3%) | 1.00 (reference) | .034* | 261.9 | 271.7 |
| T/C-C/C | 15 (16%) | 27 (28.7%) | 2.13 (1.05–4.33) | ||||
| Recessive | T/T-T/C | 94 (100%) | 93 (98.9%) | 1.00 (reference) | .25 | 265.1 | 274.8 |
| C/C | 0 (0%) | 1 (1.1%) | NA (0.00–NA) | ||||
| Overdominant | T/T-C/C | 79 (84%) | 68 (72.3%) | 1.00 (reference) | .05* | 262.6 | 272.3 |
| T/C | 15 (16%) | 26 (27.7%) | 2.02 (0.99–4.13) | ||||
| Log-additive | — | — | — | 2.15 (1.07–4.30) | .027* | 261.5 | 271.3 |
| P2 polymorphism (rs2584940) | |||||||
| Codominant | T/T | 43 (45.7%) | 27 (28.7%) | 1.00 (reference) | .039* | 261.9 | 274.9 |
| T/G | 42 (44.7%) | 52 (55.3%) | 2.00 (1.06–3.76) | ||||
| G/G | 9 (9.6%) | 15 (16%) | 2.72 (1.04–7.10) | ||||
| Dominant | T/T | 43 (45.7%) | 27 (28.7%) | 1.00 (reference) | .014* | 260.4 | 270.1 |
| T/G-G/G | 51 (54.3%) | 67 (71.3%) | 2.12 (1.16–3.89) | ||||
| Recessive | T/T-T/G | 85 (90.4%) | 79 (84%) | 1.00 (reference) | .18 | 264.6 | 274.3 |
| G/G | 9 (9.6%) | 15 (16%) | 1.82 (0.75–4.39) | ||||
| Overdominant | T/T-G/G | 52 (55.3%) | 42 (44.7%) | 1.00 (reference) | .14 | 264.3 | 274 |
| T/G | 42 (44.7%) | 52 (55.3%) | 1.54 (0.87–2.74) | ||||
| Log-additive | — | — | — | 1.74 (1.11–2.73) | .013* | 260.3 | 270 |
| P3 polymorphism (rs6756785) | |||||||
| Codominant | A/A | 50 (53.2%) | 32 (34%) | 1.00 (reference) | .03* | 261.4 | 274.4 |
| A/G | 38 (40.4%) | 54 (57.5%) | 2.21 (1.20–4.06) | ||||
| G/G | 6 (6.4%) | 8 (8.5%) | 2.09 (0.66–6.60) | ||||
| Dominant | A/A | 50 (53.2%) | 32 (34%) | 1.00 (reference) | .008* | 259.4 | 269.2 |
| A/G-G/G | 44 (46.8%) | 62 (66%) | 2.19 (1.22–3.95) | ||||
| Recessive | A/A-A/G | 88 (93.6%) | 86 (91.5%) | 1.00 (reference) | .57 | 266.1 | 275.8 |
| G/G | 6 (6.4%) | 8 (8.5%) | 1.38 (0.46–4.14) | ||||
| Overdominant | A/A-G/G | 56 (59.6%) | 40 (42.5%) | 1.00 (reference) | .02* | 261 | 270.8 |
| A/G | 38 (40.4%) | 54 (57.5%) | 1.98 (1.11–3.54) | ||||
| Log-additive | — | — | — | 1.77 (1.10–2.87) | .018* | 260.8 | 270.5 |
| P4 polymorphism (rs76968380) | |||||||
| Codominant | G/G | 88 (93.6%) | 80 (85.1%) | 1.00 (reference) | .073 | 263.2 | 276.1 |
| A/G | 6 (6.4%) | 12 (12.8%) | 2.22 (0.79–6.19) | ||||
| A/A | 0 (0%) | 2 (2.1%) | NA (0.00–NA) | ||||
| Dominant | G/G | 88 (93.6%) | 80 (85.1%) | 1.00 (reference) | .054 | 262.7 | 272.4 |
| A/G-A/A | 6 (6.4%) | 14 (14.9%) | 2.58 (0.95–7.05) | ||||
| Recessive | G/G-A/G | 94 (100%) | 92 (97.9%) | 1.00 (reference) | .095 | 263.6 | 273.3 |
| A/A | 0 (0%) | 2 (2.1%) | NA (0.00–NA) | ||||
| Overdominant | G/G-A/A | 88 (93.6%) | 82 (87.2%) | 1.00 (reference) | .13 | 264.1 | 273.9 |
| A/G | 6 (6.4%) | 12 (12.8%) | 2.16 (0.77–6.03) | ||||
| Log-additive | — | — | — | 2.58 (1.01–6.60) | .033* | 261.9 | 271.6 |
| P5 polymorphism (rs34406737) | |||||||
| Codominant | G/G | 63 (67%) | 72 (76.6%) | 1.00 (reference) | .003* | 256.9 | 269.9 |
| A/G | 31 (33%) | 17 (18.1%) | 0.48 (0.24–0.95) | ||||
| A/A | 0 (0%) | 5 (5.3%) | NA (0.00–NA) | ||||
| Dominant | G/G | 63 (67%) | 72 (76.6%) | 1.00 (reference) | .15 | 264.4 | 274.1 |
| A/G-A/A | 31 (33%) | 22 (23.4%) | 0.63 (0.33–1.19) | ||||
| Recessive | G/G-A/G | 94 (100%) | 89 (94.7%) | 1.00 (reference) | .008* | 259.4 | 269.1 |
| A/A | 0 (0%) | 5 (5.3%) | NA (0.00–NA) | ||||
| Overdominant | G/G-A/A | 63 (67%) | 77 (81.9%) | 1.00 (reference) | .02* | 261 | 270.7 |
| A/G | 31 (33%) | 17 (18.1%) | 0.45 (0.23–0.89) | ||||
| Log-additive | — | — | — | 0.86 (0.49–1.49) | .58 | 266.1 | 275.8 |
| P6 polymorphism (rs1963250) | |||||||
| Codominant | T/T | 20 (21.3%) | 37 (39.4%) | 1.00 (reference) | .016* | 260.2 | 273.1 |
| T/G | 54 (57.5%) | 46 (48.9%) | 0.46 (0.24–0.91) | ||||
| G/G | 20 (21.3%) | 11 (11.7%) | 0.30 (0.12–0.75) | ||||
| Dominant | T/T | 20 (21.3%) | 37 (39.4%) | 1.00 (reference) | .007* | 259.2 | 268.9 |
| T/G-G/G | 74 (78.7%) | 57 (60.6%) | 0.42 (0.22–0.80) | ||||
| Recessive | T/T-T/G | 74 (78.7%) | 83 (88.3%) | 1.00 (reference) | .079 | 263.3 | 273.1 |
| G/G | 20 (21.3%) | 11 (11.7%) | 0.49 (0.22–1.10) | ||||
| Overdominant | T/T-G/G | 40 (42.5%) | 48 (51.1%) | 1.00 (reference) | .25 | 265.1 | 274.8 |
| T/G | 54 (57.5%) | 46 (48.9%) | 0.71 (0.40–1.27) | ||||
| Log-additive | — | — | — | 0.53 (0.34–0.83) | .005* | 258.5 | 268.2 |
| P7 polymorphism (rs10755950) | |||||||
| Codominant | G/G | 33 (35.1%) | 31 (33%) | 1.00 (reference) | .068 | 263.1 | 276 |
| A/G | 50 (53.2%) | 40 (42.5%) | 0.85 (0.44–1.61) | ||||
| A/A | 11 (11.7%) | 23 (24.5%) | 2.19 (0.91–5.27) | ||||
| Dominant | G/G | 33 (35.1%) | 31 (33%) | 1.00 (reference) | .79 | 266.4 | 276.1 |
| A/G-A/A | 61 (64.9%) | 63 (67%) | 1.08 (0.59–1.99) | ||||
| Recessive | G/G-A/G | 83 (88.3%) | 71 (75.5%) | 1.00 (reference) | .024* | 261.3 | 271 |
| A/A | 11 (11.7%) | 23 (24.5%) | 2.42 (1.10–5.33) | ||||
| Overdominant | G/G-A/A | 44 (46.8%) | 54 (57.5%) | 1.00 (reference) | .14 | 264.3 | 274 |
| A/G | 50 (53.2%) | 40 (42.5%) | 0.65 (0.36–1.15) | ||||
| Log-additive | — | — | — | 1.34 (0.89–2.03) | .16 | 264.4 | 274.2 |
| P8 polymorphism (rs56055423) | |||||||
| Codominant | A/A | 91 (96.8%) | 81 (86.2%) | 1.00 (reference) | .023* | 260.8 | 273.8 |
| A/G | 3 (3.2%) | 12 (12.8%) | 4.44 (1.20–16.44) | ||||
| G/G | 0 (0%) | 1 (1.1%) | NA (0.00-NA) | ||||
| Dominant | A/A | 91 (96.8%) | 81 (86.2%) | 1.00 (reference) | .007* | 259.3 | 269 |
| A/G-G/G | 3 (3.2%) | 13 (13.8%) | 4.83 (1.32–17.67) | ||||
| Recessive | A/A-A/G | 94 (100%) | 93 (98.9%) | 1.00 (reference) | .23 | 265 | 274.7 |
| G/G | 0 (0%) | 1 (1.1%) | NA (0.00-NA) | ||||
| Overdominant | A/A-G/G | 91 (96.8%) | 82 (87.2%) | 1.00 (reference) | .014* | 260.4 | 270.1 |
| A/G | 3 (3.2%) | 12 (12.8%) | 4.41 (1.19–16.33) | ||||
| Log-additive | — | — | — | 4.64 (1.30–16.56) | .006* | 259 | 268.7 |
Association analysis between polymorphisms and gender incongruence. The table shows the estimation of the OR (odds ratio) for each genotype with respect to the reference genotype (1.00 (reference)) in different inheritance models (codominant, dominant, recessive, overdominant and log-additive. AIC = Akaike's information criterion; BIC = Bayesian information criterion; OR = odds ratio.
Statistically significant (P < .05).
Polymorphism Interaction Analysis With Covariate Sex
When we analyzed the interaction with the covariate sex, only P2 showed significant differences in both trans populations (women and men) (Table 4). The genotype T/G was more frequent in trans people with female natal sex than in the cis female population (OR > 2.76; P < .029) while the genotype G/G was more frequent in trans people with male natal sex than in the cis male population (OR>8.0; P < .016).
Table 4.
P2, P3, P5, P6 and P8 interaction analysis with covariate sex. The table shows the ORs (odds ratios) for the P2, P3, P5, P6 and P8 polymorphism interactions with the covariable sex. First comparing assigned female at birth (cisgender vs. transgender individuals), and assigned male at birth (cisgender vs. transgender individuals), the comparisons of the “covariate sex within each polymorphism”, and finally each “polymorphism within the covariate sex”.
| P2 and covariate sex cross-classification interaction table (n = 188, crude analysis) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|
Female |
Male |
|||||||||
| Genotypes | Cis population | Trans population | OR (95% CI) | P | Cis population | Trans population | OR (95% CI) | P | ||
| T/T | 22 | 11 | 1 | — | 21 | 16 | 1.52 (0.58-4.03) | .404 | ||
| T/G | 21 | 29 | 2.76 (1.10–6.90) | .029* | 21 | 23 | 2.19 (0.86-5.58) | .100 | ||
| G/G | 7 | 7 | 2.00 (0.56–7.15) | .289 | 2 | 8 | 8.00 (1.45-44.24) | .016* | ||
| Interaction P-value: 0.23 | ||||||||||
| Sex within P2 (n = 188, crude analysis) | ||||||||||
| Genotypes | Sex | Cis population | Trans population | OR (95% CI) | P | |||||
| T/T | female | 22 | 11 | 1 | — | |||||
| male | 21 | 16 | 1.52 (0.58–4.03) | .404 | ||||||
| T/G | female | 21 | 29 | 1 | — | |||||
| male | 21 | 23 | 0.79 (0.35–1.79) | .583 | ||||||
| G/G | female | 7 | 7 | 1 | — | |||||
| male | 2 | 8 | 4.00 (0.62–25.96) | .146 | ||||||
| Test for interaction in the trend: 0.76 | ||||||||||
| P2 within sex (n = 188, crude analysis) | ||||||||||
| Sex | Genotypes | Cis population | Trans population | OR (95% CI) | P | |||||
| T/T | 22 | 11 | 1 | — | ||||||
| female | T/G | 21 | 29 | 2.76 (1.10–6.90) | .029* | |||||
| G/G | 7 | 7 | 2.00 (0.56–7.15) | .289 | ||||||
| T/T | 21 | 16 | 1 | — | ||||||
| male | T/G | 21 | 23 | 1.44 (0.60–3.46) | .422 | |||||
| G/G | 2 | 8 | 5.25 (0.98–28.18) | .052 | ||||||
| Test for interaction in the trend: 0.23 | ||||||||||
| P3 and sex cross-classification interaction table (n = 188, crude analysis) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|
Female |
Male |
|||||||||
| Genotypes | Cis population | Trans population | OR (95% CI) | P | Cis population | Trans population | OR (95% CI) | P | ||
| A/A | 27 | 17 | 1 | — | 23 | 15 | 1.04 (0.43–2.52) | .936 | ||
| A/G | 19 | 26 | 2.17 (0.93–5.07) | .072 | 19 | 28 | 2.34 (1.01–5.43) | .046* | ||
| G/G | 4 | 4 | 1.59 (0.35–7.21) | .559 | 2 | 4 | 3.18 (0.52–19.27) | .211 | ||
| Test for interaction in the trend: 0.64 | ||||||||||
| Sex within P3 (n = 188, crude analysis) | ||||||||||
| Genotypes | Sex | Cis population | Trans population | OR (95% CI) | P | |||||
| A/A | female | 27 | 17 | 1 | — | |||||
| male | 23 | 15 | 1.04 (0.43–2.52) | .936 | ||||||
| A/G | female | 19 | 26 | 1 | — | |||||
| male | 19 | 28 | 1.08 (0.47–2.47) | .865 | ||||||
| G/G | female | 4 | 4 | 1 | — | |||||
| male | 2 | 4 | 2.00 (0.22–17.89) | .547 | ||||||
| Test for interaction in the trend: 0.64 | ||||||||||
| P3 within sex (n = 188, crude analysis) | ||||||||||
| Sex | Genotypes | Cis population | Trans population | OR (95% CI) | P | |||||
| female | A/A | 27 | 17 | 1 | — | |||||
| A/G | 19 | 26 | 2.17 (0.93–5.07) | .072 | ||||||
| G/G | 4 | 4 | 1.59 (0.35–7.21) | .559 | ||||||
| male | A/A | 23 | 15 | 1 | — | |||||
| A/G | 19 | 28 | 2.26 (0.94–5.41) | .067 | ||||||
| G/G | 2 | 4 | 3.07 (0.50–18.89) | .228 | ||||||
| Test for interaction in the trend: 0.86 | ||||||||||
| P5 and sex cross-classification interaction table (n=188, crude analysis) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|
Female |
Male |
|||||||||
| Genotypes | Cis population | Trans population | OR (95% CI) | P | Cis population | Trans population | OR (95% CI) | P | ||
| G/G | 29 | 38 | 1 | — | 34 | 34 | 0.76 (0.39–1.50) | .432 | ||
| A/G | 21 | 7 | 0.25 (0.10–0.68) | .004* | 10 | 10 | 0.76 (0.28–2.08) | .603 | ||
| A/A | 0 | 2 | — | — | 0 | 3 | — | — | ||
| Interaction P-value: 0.15 | ||||||||||
| Sex within P5 (n = 188, crude analysis) | ||||||||||
| Genotypes | Sex | Cis population | Trans population | OR (95% CI) | P | |||||
| G/G | female | 29 | 38 | 1 | — | |||||
| male | 34 | 34 | 0.76 (0.39–1.50) | .432 | ||||||
| A/G | female | 21 | 7 | 1 | — | |||||
| male | 10 | 10 | 3.00 (0.88–10.21) | .078 | ||||||
| A/A | female | 0 | 2 | 1 | — | |||||
| male | 0 | 3 | 1 | — | ||||||
| Test for interaction in the trend: 0.044* | ||||||||||
| P5 within sex (n = 188, crude analysis) | ||||||||||
| Sex | Genotypes | Cis population | Trans population | OR (95% CI) | P | |||||
| female | G/G | 29 | 38 | 1 | — | |||||
| A/G | 21 | 7 | 0.25 (0.10–0.68) | .004* | ||||||
| A/A | 0 | 2 | — | — | ||||||
| male | G/G | 34 | 34 | 1 | — | |||||
| A/G | 10 | 10 | 1.00 (0.37–2.71) | 1 | ||||||
| A/A | 0 | 3 | — | — | ||||||
| Test for interaction in the trend: 0.15 | ||||||||||
| P6 and sex cross-classification interaction table (n=188, crude analysis) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|
Female |
Male |
|||||||||
| Genotypes | Cis population | Trans population | OR (95% CI) | P | Cis population | Trans population | OR (95% CI) | P | ||
| T/T | 10 | 15 | 1 | — | 10 | 22 | 1.47 (0.49–4.38) | .500 | ||
| T/G | 31 | 23 | 0.49 (0.19–1.30) | .146 | 23 | 23 | 0.67 (0.25–1.79) | .433 | ||
| G/G | 9 | 9 | 0.67 (0.20–2.26) | .528 | 11 | 2 | 0.12 (0.02–0.67) | .017* | ||
| Interaction P-value: .074 | ||||||||||
| Sex within P6 (n = 188, crude analysis) | ||||||||||
| Genotypes | Sex | Cis population | Trans population | OR (95% CI) | P | |||||
| T/T | female | 10 | 15 | 1 | — | |||||
| male | 10 | 22 | 1.47 (0.49–4.38) | .500 | ||||||
| T/G | female | 31 | 23 | 1 | — | |||||
| male | 23 | 23 | 1.35 (0.61–2.97) | .466 | ||||||
| G/G | female | 9 | 9 | 1 | — | |||||
| male | 11 | 2 | 0.18 (0.03–1.06) | .058 | ||||||
| Test for interaction in the trend: 0.072 | ||||||||||
| P6 within sex (n = 188, crude analysis) | ||||||||||
| Sex | Genotypes | Cis population | Trans population | OR (95% CI) | P | |||||
| female | T/T | 10 | 15 | 1 | — | |||||
| T/G | 31 | 23 | 0.49 (0.19–1.30) | .146 | ||||||
| G/G | 9 | 9 | 0.67 (0.20–2.26) | .528 | ||||||
| male | T/T | 10 | 22 | 1 | — | |||||
| T/G | 23 | 23 | 0.45 (0.18–1.17) | .094 | ||||||
| G/G | 11 | 2 | 0.08 (0.02–0.44) | .001* | ||||||
| Test for interaction in the trend: 0.074 | ||||||||||
| P8 and sex cross-classification interaction table (n = 188, crude analysis) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|
Female |
Male |
|||||||||
| Genotypes | Cis population | Trans population | OR (95% CI) | P | Cis population | Trans population | OR (95% CI) | P | ||
| A/A | 49 | 43 | 1 | — | 42 | 38 | 1.03 (0.57–1.88) | .929 | ||
| A/G | 1 | 3 | 3.42 (0.34–34.10) | .299 | 2 | 9 | 5.13 (1.05–25.05) | .042* | ||
| G/G | 0 | 1 | — | — | 0 | 0 | — | — | ||
| Interaction P-value: .8 | ||||||||||
| Sex within P8 (n = 188, crude analysis) | ||||||||||
| Genotypes | Sex | Cis population | Trans population | OR (95% CI) | P | |||||
| A/A | female | 49 | 43 | 1 | — | |||||
| male | 42 | 38 | 1.03 (0.57–1.88) | .929 | ||||||
| A/G | female | 1 | 3 | 1 | — | |||||
| male | 2 | 9 | 1.50 (0.10–23.07) | .782 | ||||||
| G/G | female | 0 | 1 | 1 | — | |||||
| male | 0 | 0 | — | — | ||||||
| Test for interaction in the trend: 0.89 | ||||||||||
| P8 within sex (n = 188, crude analysis) | ||||||||||
| Sex | Genotypes | Cis population | Trans population | OR (95% CI) | P | |||||
| female | A/A | 49 | 43 | 1 | — | |||||
| A/G | 1 | 3 | 3.42 (0.34–34.10) | .299 | ||||||
| G/G | 0 | 1 | — | — | ||||||
| male | A/A | 42 | 38 | 1 | — | |||||
| A/G | 2 | 9 | 4.97 (1.01–24.48) | .048* | ||||||
| G/G | 0 | 0 | — | — | ||||||
| Test for interaction in the trend: .8 | ||||||||||
Statistically significant (P < .05).
The other polymorphisms (P3, P5, P6, and P8) showed significant differences in the distribution of the genotypes only in the population with male natal sex (Table 4), while the P5 showed the significant difference only in the female natal sex.
Haplotype Analysis
For polymorphisms located in SRC-1 (Table 5), the T allele for P1 was linked to the T allele for P2, and to the A allele for P3 (haplotype 1: T-T-A) with a total frequency of 0.45 (Table 5). However, the C allele for P1 was linked to the G allele for P2 and to the A allele for P3 (haplotype 5: C-G-A) (OR > 2.62; P < .05) or to the G allele for P3 (haplotype 7: C-G-G) (P < .0001) (Table 5), with a global haplotype association P < 0.009.
Table 5.
Haplotype analysis for polymorphisms located in SRC-1 (P1, P2 and P3 polymorphisms)
| Haplotype frequencies estimation and haplotype association with response (n = 188, adjusted by sex) | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Haplotypes | P1 | P2 | P3 | Total | Cis population | Trans population | Cumulative frequency | OR (95% CI) | P-value |
| 1 | T | T | A | 0.4501 | 0.5201 | 0.377 | 0.4501 | 1.00 (reference) | — |
| 2 | T | T | G | 0.1495 | 0.134 | 0.1699 | 0.5996 | 2.25 (0.99–5.13) | .054 |
| 3 | T | G | G | 0.147 | 0.1319 | 0.1601 | 0.7466 | 1.73 (0.81–3.71) | .16 |
| 4 | T | G | A | 0.139 | 0.1341 | 0.144 | 0.8856 | 1.80 (0.81–3.97) | .15 |
| 5 | C | G | A | 0.069 | 0.0531 | 0.0897 | 0.9546 | 2.62 (1.00–6.83) | .05* |
| 6 | C | T | A | 0.0228 | 0.0267 | 0.0169 | 0.9774 | 1.39 (0.23–8.34) | .72 |
| 7 | C | G | G | 0.0226 | 0 | 0.0423 | 1 | 379142884.10 (379142883.16–379142885.04) | <.0001*† |
| Global haplotype association P-value: .009* | |||||||||
The risk for each haplotype is compared with regards to the reference category (1.00 reference); OR = Odds ratio.
Statistically significant (P < .05).
Statistically significant after Bonferroni correction (P < .05/157 = .0003).
For polymorphisms located in SRC-2 (Table 6), the significant haplotypes were haplotype 2: (G-G-T-A-A) (OR > 2.49; P < .02), and the haplotype 8: (G-G-T-A-G) (OR > 12.86; P < .028) (Table 6), with a global haplotype association P < .005.
Table 6.
Haplotype analysis for polymorphisms located in SRC-2 (P4, P5, P6, P7 and P8 polymorphisms)
| Haplotype frequencies estimation and haplotype association with response (n = 188, adjusted by sex) | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Haplotypes | P4 | P5 | P6 | P7 | P8 | Total | Cis population | Trans population | Cumulative frequency | OR (95% CI) | P-value |
| 1 | G | G | G | G | A | 0.2546 | 0.3239 | 0.1963 | 0.2546 | 1.00 (reference) | — |
| 2 | G | G | T | A | A | 0.2206 | 0.2142 | 0.236 | 0.4752 | 2.49 (1.16–5.34) | .02* |
| 3 | G | G | T | G | A | 0.2022 | 0.1721 | 0.2303 | 0.6773 | 2.00 (0.93–4.31) | .079 |
| 4 | G | G | G | A | A | 0.0891 | 0.0861 | 0.0793 | 0.7664 | 1.05 (0.38–2.88) | .92 |
| 5 | G | A | G | G | A | 0.0474 | 0.0656 | 0.0235 | 0.8138 | 0.55 (0.11–2.89) | .48 |
| 6 | G | A | T | A | A | 0.0419 | 0.0474 | 0.0423 | 0.8557 | 1.11 (0.24–5.24) | .89 |
| 7 | G | A | T | G | A | 0.041 | 0.0393 | 0.0426 | 0.8967 | 3.00 (0.10–86.09) | .52 |
| 8 | G | G | T | A | G | 0.0217 | 0 | 0.036 | 0.9184 | 12.86 (1.34–123.38) | .028* |
| 9 | A | G | T | G | A | 0.0173 | 0.0085 | 0.0228 | 0.9357 | 5.62 (0.56–56.71) | .15 |
| 10 | A | G | G | G | A | 0.0165 | 0.0077 | 0.0205 | 0.9522 | 3.53 (0.40–31.50) | .26 |
| 11 | G | A | T | A | G | 0.0138 | 0.0028 | 0.0189 | 0.9659 | 2.68 (0.27–26.20) | .4 |
| 12 | A | G | T | A | A | 0.0108 | 0.0158 | 0.0093 | 0.9767 | 0.00 (-Inf–Inf) | 1 |
| rare | * | * | * | * | * | 1 | 26887674246665641394185292538194458249584765033713636843978752.00 (26887674246622846799367197037120806603076791371544336569204736.00 - 26887674246708435989003388039268109896092738695882937118752768.00) | <.0001*† | |||
| Global haplotype association P-value: .005* | |||||||||||
The risk for each haplotype is compared with regards to the reference category (1.00 reference); OR = Odds ratio.
Statistically significant (P < .05).
Statistically significant after Bonferroni correction (P < .05/157 = .0003).
DISCUSSION
The estrogen receptors α and β, in addition to hormonal receptors, are also transcription factors that, when exposed to their ligand, dimerize and form complexes, binding to coactivator proteins36 (Figure 1), modifying the transcription of multiple target genes in cascade mode37 and, ultimately, the neuronal function. Therefore, coactivators are proteins that influence the ability of the transcription factors to activate or inhibit expression of multiple genes.26 Some coactivators for sex steroids receptors are SRC-1, SRC-2, and SRC-3.23 Given the intimate relationship between sex steroids and brain dimorphism, and sex steroids and gene transcription, it seems is clear that we can to postulate the implication of the DNA coactivators in the process of brain dimorphism.
In our study, we analyzed the allele and genotype frequencies, the association with gender incongruence, the interactions with the covariate sex, and the linkage disequilibrium of 157 polymorphisms located at the coactivators SRC-1, SRC-2, and SRC-3 in a population of 94 transgender individuals versus 94 cis gender individuals. We found significant differences in eight polymorphisms located in SRC-1 and SRC-2. Furthermore, only P2 (rs2584940) in SRC-1 showed significant differences in the interaction analysis with covariate “sex”. When the analysis was carried out in separate populations according to their natal sex, we found that polymorphisms P2 and P5 were statistically significant for female natal sex populations, while P2, P3, P6, and P8 were statistically significant for male natal sex populations (Table 4). The SRC-1 haplotypes C-G-A and C-G-G and the SRC-2 haplotypes G-G-T-A-A and G-G-T-A-G were more frequent in the trans population and showed statistical significance.
Based on experiments in rodents, it is believed that male sexual differentiation of the brain is caused by androgens, after conversion to estrogens by the aromatase. Moreover, observations in human subjects show that the direct effects of testosterone on the developing fetal brain and also during puberty, are of great importance for the development of male gender identity.38 However, in the analysis that our group carried out on androgen coactivators (NCOA-4), we did not find any significant differences (data not shown).
Our data are in concordance with recent work that showed that the nuclear receptor coactivators, SRC-1 and SRC-2, are essential for efficient ER transcriptional activity in brain.39 Furthermore, SRC-1 and SRC-2 are distributed in several specific areas of the brain in different proportions, such as the hypothalamus and the hippocampus, showing at the same time, differences in the binding preference to ER α or β subtypes when located in different brain regions.39,40 For example, SRC-1 from the hippocampus interacts equally with ERα and ERβ, while SRC-1 obtained from hypothalamus interacts more with ERα than with ERβ. On the other hand, SRC-2 interacts with ERα in the hippocampus but, in contrast, did not interact with ERβ under any ligand condition.
These differential interactions of SRC-1 and SRC-2 with the ER subtypes suggest that these brain regions have distinct expression patterns of coregulators. Understanding how nuclear receptor coactivators' function with various steroid receptors is critical to understanding how the hormones act in different brain regions.
Moreover, our results are also in concordance with the study of the functional significance of the nuclear receptor coactivator SRC-1 in the developing brain.41 The authors, Auger et al, investigated the consequence of reducing SRC-1 protein during sexual differentiation of the brain, and reported that reducing this protein interferes with the defeminizing actions of estrogen in neonatal rat brains. Their data indicated that SRC-1 expression is critically involved in the hormone-dependent development of normal male reproductive behavior and brain morphology.
Consequently, our data are in agreement with the results of Auger et al,41 since the polymorphic analysis of this coactivator showed significant differences when allelic and genotypic frequencies were analyzed. Furthermore, the P2 polymorphism, located in SRC-1, also showed statistically significant interactions with the covariate "sex."
One of the limitations of our study is that the sample analyzed is small and not all P values pass the Bonferroni correction. To make our study more robust, it would be necessary to analyze a larger sample, or validate the conclusions with a new analysis from another trans population.
In conclusion, our results have shown that the coactivators, SRC-1 and SRC-2 could be considered as candidates for increasing the list of potential “susceptibility” genes for gender incongruence. Furthermore, our data continue to support the hypothesis that gender incongruence is a multifactorial complex trait, involving intricate interactions among sex steroids, sex steroids receptors, coactivators, and multiple other genes and polymorphisms.
STATEMENT OF AUTHORSHIP
Category 1: a) Conception and Design: Rosa Fernández and Eduardo Pásaro, b) Acquisition of Data: Enrique Delgado-Zayas, Karla Ramírez, c) Resources: Esther Gómez Gil, Isabel Esteva, d) Analysis and Interpretation of Data: Rosa Fernández and Eduardo Pásaro; Category 2: a) Drafting the Article: Karla del Valle Ramírez, Rosa Fernández, Eduardo Pásaro, Antonio Guillamon, Enrique Delgado-Zayas, Esther Gómez-Gil, Isabel Esteva. b) Revising It for Intellectual Content: Rosa Fernández, Eduardo Pásaro, Esther Gómez Gil and Antonio Guillamon; Category 3: a) Final Approval of the Completed Article: Rosa Fernández, Enrique Delgado-Zayas, Karla Ramírez, Esther Gómez-Gil, Isabel Esteva, Antonio Guillamón, Eduardo Pásaro.
Acknowledgment
We are grateful to everyone who contributed to the study, and to the trans and cis individuals who participated in particular.
Footnotes
Conflict of Interest: The authors report no conflicts of interest.
Funding: This work was supported by grants: ED431B 019/02 (EP), PGC2018-094919-B-C21 (AG), PGC2018-094919-B-C22 (RF and EP).
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