Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-10T07:08:53.516Z Has data issue: false hasContentIssue false
  • English
  • Français

Alterations in the inferior fronto-occipital fasciculus – a specific neural correlate of gender incongruence?

Published online by Cambridge University Press:  18 March 2022

Jason van Heesewijk Open the ORCID record for Jason van Heesewijk [Opens in a new window] ,
Martijn D. Steenwijk ,
Baudewijntje P. C. Kreukels ,
Dick J. Veltman ,
Julie Bakker  and
Sarah M. Burke
Jason van Heesewijk*
Affiliation:
Center of Expertise on Gender Dysphoria, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1131, Amsterdam, Noord-Holland, Netherlands
Martijn D. Steenwijk
Affiliation:
Center of Expertise on Gender Dysphoria, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1131, Amsterdam, Noord-Holland, Netherlands
Baudewijntje P. C. Kreukels
Affiliation:
Center of Expertise on Gender Dysphoria, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1131, Amsterdam, Noord-Holland, Netherlands
Dick J. Veltman
Affiliation:
Center of Expertise on Gender Dysphoria, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1131, Amsterdam, Noord-Holland, Netherlands
Julie Bakker
Affiliation:
Center of Expertise on Gender Dysphoria, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1131, Amsterdam, Noord-Holland, Netherlands
Sarah M. Burke*
Affiliation:
Center of Expertise on Gender Dysphoria, Amsterdam University Medical Centers, location VUmc, De Boelelaan 1131, Amsterdam, Noord-Holland, Netherlands
*
Authors for correspondence: Jason van Heesewijk, E-mail: jason@l3q.nl; Sarah M. Burke, E-mail: sarahburke82@gmail.com
Authors for correspondence: Jason van Heesewijk, E-mail: jason@l3q.nl; Sarah M. Burke, E-mail: sarahburke82@gmail.com
Rights & Permissions [Opens in a new window]

Abstract

Background

Increasing numbers of adolescents seek help for gender-identity questions. Consequently, requests for medical treatments, such as puberty suppression, are growing. However, studies investigating the neurobiological substrate of gender incongruence (when birth-assigned sex and gender identity do not align) are scarce, and knowledge about the effects of puberty suppression on the developing brain of transgender youth is limited.

Methods

Here we cross-sectionally investigated sex and gender differences in regional fractional anisotropy (FA) as measured by diffusion MR imaging, and the impact of puberty on alterations in the white-matter organization of 35 treatment-naive prepubertal children and 41 adolescents with gender incongruence, receiving puberty suppression. The transgender groups were compared with 79 age-matched, treatment-naive cisgender (when sex and gender align) peers.

Results

We found that transgender adolescents had lower FA in the bilateral inferior fronto-occipital fasciculus (IFOF), forceps major and corpus callosum than cisgender peers. In addition, average FA values of the right IFOF correlated negatively with adolescents' cumulative dosage of puberty suppressants received. Of note, prepubertal children also showed significant FA group differences in, again, the right IFOF and left cortico-spinal tract, but with the reverse pattern (transgender > cisgender) than was seen in adolescents.

Conclusions

Importantly, our results of lower FA (indexing less longitudinal organization, fiber coherence, and myelination) in the IFOF of gender-incongruent adolescents replicate prior findings in transgender adults, suggesting a salient neural correlate of gender incongruence. Findings highlight the complexity with which (pubertal) sex hormones impact white-matter development and add important insight into the neurobiological substrate associated with gender incongruence.

Keywords

Fractional anisotropygender incongruencegendergonadotropin-releasing hormone analogsinferior fronto-occipital fasciculuspubertysex
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 8 , June 2023 , pp. 3461 - 3470
Check for updates
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Introduction

Gender identity (e.g. male, female, non-binary, genderqueer) is a uniquely human trait that develops during childhood (Halim & Ruble, Reference Halim and Ruble2010). Biological and sociocultural factors (family, peers, society) are thought to shape individual differences in the subjective experience of a child's gender (Fausto-Sterling, Reference Fausto-Sterling2019). Gender identity is refined further during adolescence, a period of significant (physical, cognitive, and social-emotional) developmental changes. Within the context of the dramatic rise of pubertal sex hormone levels impacting an adolescent's body in a sex-specific way, and in relation to the emerging, yet not clearly formed sexual identity, gender identity is further differentiated (Ruble, Martin, & Berenbaum, Reference Ruble, Martin and Berenbaum2006). For most individuals, birth-assigned sex and gender identity are overall congruent (i.e. cisgender). However, for individuals identifying as transgender, sex and gender do not align. Transgender individuals may meet the diagnostic criteria for gender incongruence (World Health Organization, 2018), which is defined as a marked feeling of incongruence between one's sex assigned at birth and one's experienced gender.

In recent years, exponential increases in referrals of adolescents to specialized gender identity services have been reported worldwide (Pang et al., Reference Pang, de Graaf, Chew, Hoq, Keith, Carmichael and Steensma2020; Zucker, Reference Zucker2019). The ongoing increase in requests for medical treatments (such as puberty suppression and gender-affirming hormone treatment) of transgender youth asks for further examination of the development of gender identity and knowledge about the effects of puberty suppression on the developing brain.

A prominent hypothesis on the etiology of gender incongruence proposes that divergent early sexual differentiation mediates sex-atypical organization of the brain, and thereby the development of a gender identity not aligning with one's sex (Dörner, Reference Dörner1988; Swaab & Hofman, Reference Swaab and Hofman1995; Zhou, Hofman, Gooren, & Swaab, Reference Zhou, Hofman, Gooren and Swaab1995). Partial support for the sexual differentiation hypothesis, which was recently refined (Guillamon, Junque, & Gómez-Gil, Reference Guillamon, Junque and Gómez-Gil2016; Uribe et al., Reference Uribe, Junque, Gómez-Gil, Abos, Mueller and Guillamon2020), has since been provided by several magnetic resonance imaging (MRI) studies (Manzouri & Savic, Reference Manzouri and Savic2019; also see reviews by Kreukels & Guillamon, Reference Kreukels and Guillamon2016; Nguyen et al., Reference Nguyen, Loughead, Lipner, Hantsoo, Kornfield and Epperson2019). One of these MRI measures, used to characterize white-matter microstructure by means of Diffusion Tensor Imaging (DTI), is fractional anisotropy (FA). Relatively higher overall, as well as region-specific FA values have been found in cisgender men compared to cisgender women (Bava et al., Reference Bava, Boucquey, Goldenberg, Thayer, Ward, Jacobus and Tapert2011; Cox et al., Reference Cox, Ritchie, Tucker-Drob, Liewald, Hagenaars, Davies and Deary2016; Den Braber et al., Reference Den Braber, Van't Ent, Stoffers, Linkenkaer-Hansen, Boomsma and De Geus2013; Hsu et al., Reference Hsu, Leemans, Bai, Lee, Tsai, Chiu and Chen2008; Inano, Takao, Hayashi, Abe, & Ohtomo, Reference Inano, Takao, Hayashi, Abe and Ohtomo2011; Menzler et al., Reference Menzler, Belke, Wehrmann, Krakow, Lengler, Jansen and Knake2011; van Hemmen et al., Reference van Hemmen, Saris, Cohen-Kettenis, Veltman, Pouwels and Bakker2016), indexing relatively more longitudinal organization, fiber coherence, and myelination in males, [but see Kochunov et al. (Reference Kochunov, Jahanshad, Marcus, Winkler, Sprooten, Nichols and Van Essen2015), who found higher FA values in females than males].

Comparing transgender individuals with cisgender controls, higher, thus masculinized FA values in a group of 18 transgender men (female sex assigned at birth, identifying as male) were found, whereas 18 transgender women (male sex assigned at birth, identifying as female) had intermediate FA values not showing significant differences from either of the cisgender groups (Rametti et al., Reference Rametti, Carrillo, Gomez-Gil, Junque, Segovia, Gomez and Guillamon2011a; Reference Rametti, Carrillo, Gomez-Gil, Junque, Zubiarre-Elorza, Segovia and Guillamon2011b). Similarly, a study by Kranz et al. (Reference Kranz, Hahn, Kaufmann, Küblböck, Hummer, Ganger and Lanzenberger2014) reported that transgender women and transgender men had parameters in between those of the two cisgender-control groups, thus diverging from their birth-assigned sex. More recently, sex by gender identity interaction in FA values was found specifically in the right inferior fronto-occipital fasciculus (IFOF, see Fig. 1 for an anatomical representation of the bilateral IFOF; Burke, Manzouri, & Savic, Reference Burke, Manzouri and Savic2017). This tract connects occipital with frontal brain regions, carrying visual perceptual information to higher-order cognitive brain regions of the prefrontal cortex (Catani, Reference Catani2006, Reference Catani2007). The interaction effect revealed lower, thus sex-atypical FA values, in 27 transgender women compared with 29 homosexual and 40 heterosexual cisgender men (Burke et al., Reference Burke, Manzouri and Savic2017). Interestingly, the effect was, thus, irrespective of sexual orientation. Therefore, the alterations in white-matter microstructure were specifically related to group differences in gender identity. However, in contrast to prior studies (Kranz et al., Reference Kranz, Hahn, Kaufmann, Küblböck, Hummer, Ganger and Lanzenberger2014; Rametti et al., Reference Rametti, Carrillo, Gomez-Gil, Junque, Segovia, Gomez and Guillamon2011a, Reference Rametti, Carrillo, Gomez-Gil, Junque, Zubiarre-Elorza, Segovia and Guillamon2011b), no group differences were found in the birth-assigned females. Overall, the trans- v. cisgender group differences in earlier studies were found prior to any hormonal treatment, suggesting a priori sex-atypical differentiation of brain structures in adult individuals with gender incongruence.

Fig. 1. Anatomical representation of the Inferior Frontal Occipital Fasciculus in (a) sagittal and (b) transverse radiological display orientation. The bilateral IFOF was selected from the JHU white-matter tractography atlas (Mori, Wakana, van Zijl, & Nagae-Poetscher, Reference Mori, Wakana, Nagae-Poetsche and van Zijl2005) and overlayed on the FMRIB58_FA_1 mm standard space image. The figure was created using FSL image viewer FSLeyes.

In addition, pubertal development (Bava et al., Reference Bava, Boucquey, Goldenberg, Thayer, Ward, Jacobus and Tapert2011; Chahal et al., Reference Chahal, Vilgis, Grimm, Hipwell, Forbes, Keenan and Guyer2018; Genc et al., Reference Genc, Seal, Dhollander, Malpas, Hazell and Silk2017; Schmithorst, Holland, & Dardzinski, Reference Schmithorst, Holland and Dardzinski2008), as well as sex hormones (Herting, Maxwell, Irvine, & Nagel, Reference Herting, Maxwell, Irvine and Nagel2012; Ho et al., Reference Ho, Colich, Sisk, Oskirko, Jo and Gotlib2020; Pangelinan et al., Reference Pangelinan, Leonard, Perron, Pike, Richer, Veillette and Paus2016; Peper et al., Reference Peper, Mandl, Braams, de Water, Heijboer, Koolschijn and Crone2013; Peper, de Reus, van den Heuvel, & Schutter, Reference Peper, de Reus, van den Heuvel and Schutter2015) have been differentially associated with white-matter diffusion characteristics in male and female adolescents. A 2-year longitudinal study in adolescents (two visits, age at first visit 10–18 years) showed FA increases in cisgender boys and decreases in cisgender girls that were predicted by adrenal- and gonadal hormone-based changes (Herting et al., Reference Herting, Kim, Uban, Kan, Binley and Sowell2017). This suggests that puberty, independently of chronological age, influences brain development in a sex-specific way.

Lastly, a prospective case study of an 11-year-old transgender girl who received puberty suppression treatment, showed that the typical, testosterone-related white-matter maturation (i.e. increase in FA with older age) was not observed (Schneider et al., Reference Schneider, Spritzer, Soll, Fontanari, Carneiro, Tovar-Moll and Lobato2017). In addition, performance intelligence quotient and memory deteriorated over a period of 28 months. These single-case findings warrant further study of the effects of the puberty suppression treatment in transgender adolescents on white-matter development and cognitive functioning in larger samples.

In the current study, we investigated the hypothesized sex-atypical (Burke et al., Reference Burke, Manzouri and Savic2017; Kranz et al., Reference Kranz, Hahn, Kaufmann, Küblböck, Hummer, Ganger and Lanzenberger2014; Rametti et al., Reference Rametti, Carrillo, Gomez-Gil, Junque, Segovia, Gomez and Guillamon2011a, Reference Rametti, Carrillo, Gomez-Gil, Junque, Zubiarre-Elorza, Segovia and Guillamon2011b), and transgender-specific (Burke et al., Reference Burke, Manzouri and Savic2017) differences in white-matter microstructure in relation to pubertal status, using a targeted region-of-interest approach. We included a sample of pre-pubertal children and adolescents who were referred to a gender-identity clinic, and applied identical analysis settings as in Burke et al. (Reference Burke, Manzouri and Savic2017) to ensure the highest possible comparability and to replicate previous findings in a younger, independent sample.

Methods

Participants

In a total of 82 children and 82 adolescents DTI data, among other (f)MRI paradigms (see Burke, Cohen-Kettenis, Veltman, Klink, & Bakker, Reference Burke, Cohen-Kettenis, Veltman, Klink and Bakker2014; Nota et al., Reference Nota, Kreukels, den Heijer, Veltman, Cohen-Kettenis, Burke and Bakker2017) were acquired. Due to insufficient data quality (because of e.g. artefacts, reconstruction errors; N = 4), insufficient data quality due to head motion (determined by visual inspection; N = 4), and lack of time to finish the MRI sessionFootnote †Footnote 1 (N = 1), data of nine children had to be excluded, leaving datasets of 73 children and 82 adolescents for further analysis (see below for acquisition parameters).

Twenty prepubertal transgender girls (Mage = 10.4, s.d. = 0.8), 15 prepubertal transgender boys (Mage = 9.6, s.d. = 1.2), 20 adolescent transgender girls (Mage = 15.4, s.d. = 1.1), and 21 adolescent transgender boys (Mage = 16.1, s.d. = 0.8) were all diagnosed with gender incongruence-related diagnosis (at the time of inclusion the DSM-IV-TR criteria applied) and recruited via the Center of Expertise on Gender Dysphoria at the Amsterdam University Medical Centers, location VUmc in Amsterdam, the Netherlands. The prepubertal groups were treatment-naive at the time of the study. All adolescent participants with gender incongruence had been treated with monthly 3.75 mg Triptorelin (Decapeptyl-CR®, Ferring, Hoofddorp, the Netherlands) injections for, on average, 22.7 months (range 2–48 months) resulting in complete suppression of gonadal hormone production (Kreukels & Cohen-Kettenis, Reference Kreukels and Cohen-Kettenis2011).

The control groups, 18 prepubertal cisgender boys (Mage = 9.5, s.d. = 1.0), 20 prepubertal cisgender girls (Mage = 9.8, s.d. = 0.9), 20 adolescent cisgender boys (Mage = 15.9, s.d. = 0.6) and 21 adolescent cisgender girls (Mage = 16.3, s.d. = 1.0), were recruited via several secondary schools in the Netherlands, and by inviting friends of the participants with gender incongruence.

Details of the assessments of puberty stage, hormone analyses, MR image acquisition and preprocessing steps are described in the Supplementary Materials.

Statistical analyses

Sample characteristics

Using the Statistical Package for the Social Sciences, version 25.0 (SPSS Inc., Chicago, IL, USA), we compared age between groups by means of one-way ANOVAs and Tanner stage between groups by means of chi-square tests. FA-residual distributions were tested for normality by means of Kolmogorov–Smirnov tests and residual histograms and Q-Q plots. All results were considered significant at p < 0.05 and/ or η2 > 0.13 (medium effect size; Field, Reference Field2013) unless otherwise stated.

FA in relation to sex, gender, and pubertal status

To assess main and interaction effects of and between Sex, Gender and/or Pubertal status, we conducted a factorial multivariate analysis of variance (factorial MANOVA) with average FA values of all (N = 13) tracts as dependent variables, and Sex, Gender and Pubertal status (prepubertal; adolescent) as independent variables. Similar effects per tract were analyzed using separate univariate ANOVAs and Post-hoc one-way ANOVAs with planned contrasts were conducted to compare individual tract average FA values of transgender boys and girls with those of their birth-assigned-sex cisgender control group.

Covarying individual differences in pubertal stage

Pubertal stages (according to Marshall & Tanner, Reference Marshall and Tanner1969, Reference Marshall and Tanner1970) were added to the model as covariates in secondary analyses using Sex by Gender factorial MANOVA among the prepubertal and adolescent sub-sample separately. Univariate ANOVAs and Post-hoc independent factorial ANOVAs were again used to differentiate between tracts and sex/gender groups, respectively.

FA in relation to puberty suppression

Lastly, we conducted exploratory correlation analyses between average FA values (of those tracts that showed effects in the main analyses) and the cumulative doses of GnRHa received by the adolescent transgender girls and boys. Results were Bonferroni corrected for multiple testing (adjusted α = 0.05/4 tracts tested = 0.0125).

Results

Sample characteristics

Demographic information, including age, hormone levels, and Tanner stages for all groups is provided in Table 1. Among the children as well as the adolescents, significant age differences were found between groups, F (3, 68) = 3.0, p = 0.038, and F (3, 78) = 4.2, p = 0.008, respectively. However, post-hoc Bonferroni-corrected comparisons did not reveal significant age differences between groups of the same birth-assigned sex. By design, the groups differed in terms of Pubertal status. Almost all children were prepubertal and thus had Tanner stages of 1 for pubic hair and breast/genital development (see Table 1). Six children had Tanner stage 2 for pubic hair (three cisgender girls) or breast/genitals (one cisgender girl, one transgender girl, and one transgender boy), but were nevertheless included in the prepubertal group. All adolescents were pubertal [Tanner stages ranged from 2 to 6, except one transgender girl who had received GnRHa early on and had no pubic hair (Tanner P = 1)] and Tanner stages differed significantly between the groups for pubic hair (χ2 (15) = 36.9, p = 0.001) and breasts/genitals (χ2 (9) = 24.4, p = 0.004); transgender girls had significantly lower Tanner stages than the other adolescent groups.

Table 1. Subject characteristics per group

Continuous data are presented as median (s.d.), Tanner stages as median (range). Luteinizing hormone (LH), follicle-stimulating hormone (FSH), dehydroepiandrosterone (DHEA), and Estradiol are corrected for creatinine. Tanner P = pubic hair stage, Tanner M or G = breast or genital stage, *Post-hoc Bonferroni corrected comparisons revealed no age differences between the same birth-assigned sex groups (i.e. cisgender boys v. transgender girls, and cisgender girls v. transgender boys), only adolescent transgender girls were significantly younger than adolescent cisgender girls. $Six children had Tanner stage 2 for pubic hair (three cisgender girls) or breast/genitals (one cisgender girl, transgender girl, and transgender boy). Bold typeface = p <0.05.

FA in relation to sex, gender, and pubertal status

FA values per group and tract are provided in the supplementary materials – Table S2. Assumptions for normality of FA-residual distributions were met. The Sex (birth-assigned female; male) by Gender (female; male) by Pubertal status (prepubertal; adolescent) factorial MANOVA revealed, using Wilks' Lambda, an overall (across all tracts) significant main effect of Pubertal status, ∧ = 0.10, F (13, 135) = 98.2, p < 0.001. An interaction effect of Sex and Gender (∧ = 0.82, F (13, 135) = 2.1, p = 0.012) showed that, across all tracts examined and in both age groups, cisgender and transgender individuals differed in the white-matter organization. An additional three-way interaction effect of Pubertal status, Sex and Gender (∧ = 0.83, F (13, 135) = 2.1, p = 0.018) indicated that the pattern of cis- v. transgender group differences was different for the prepubertal v. adolescent groups. No overall main effects of Sex or Gender, and no interaction effect between Pubertal status and Sex, or Pubertal status and Gender were found.

Separate univariate ANOVAs on the tracts showed effects of Pubertal status in all tracts, with higher FA values in adolescents than in children. In contrast to the overall effects, no interaction effect between Sex and Gender was revealed in any of the tracts separately, and a main effect of Sex was shown for two major long white-matter tracts; right superior longitudinal fasciculus (RSLF), F (1, 147) = 4.2, p = 0.042, η 2 = 0.03, and left cortico-spinal tract (LCST), F (1, 147) = 6.1, p = 0.015, η 2 = 0.04, with higher FA values in birth-assigned boys compared to birth-assigned girls. No effect of Gender was revealed, nor an interaction effect of Sex and Gender, Pubertal status and Sex, or Pubertal status and Gender (see Fig. 2a–f).

Fig. 2. Boxplots showing fractional anisotropy (FA) values per tract (a–f). Group differences were analyzed with: (1) Sex (birth-assigned female/male) by Gender identity (female/male) by Pubertal status (prepubertal/adolescent) factorial MANOVA including all cisgender and transgender groups without covariates. Here * denotes significant three-way interaction effects of Sex, Gender and Pubertal status (LIFOF, F (1, 147) = 7.4, p = 0.007, η 2 = 0.05; RIFOF, F (1, 147) = 4.5, p = 0.036, η 2 = 0.03; forceps major, F (1, 147) = 4.6, p = 0.033, η 2 = 0.03), ** main effects of Pubertal status (LCST, F (1, 147) = 106.3, η 2 = 0.42; RCST, F (1, 147) = 51.9, η 2 = 0.26; Forceps major, F (1, 147) = 150.8, η 2 = 0.51; Forceps minor, F (1, 147) = 183.9, η 2 = 0.56; LIFOF, F (1, 147) = 371.4, η 2 = 0.72; RIFOF, F (1, 147) = 150.3, η 2 = 0.51; LILF, F (1, 147) = 412.7, η 2 = 0.74; RILF, F (1, 147) = 136.9, η 2 = 0.48; LSLF, F (1, 147) = 280.7, η 2 = 0.66; RSLF, F (1, 147) = 149.9, η 2 = 0.51; Genu of CC, F (1, 147) = 13.6, η 2 = 0.09; Body of CC, F (1, 147) = 68.4, η 2 = 0.32; Splenium of CC, F (1, 147) = 271.0, η 2 = 0.65. All p < 0.001), and *** main effects of Sex (LCST, F (1, 147) = 6.1, p = 0.015, η 2 = 0.04; RSLF, F (1, 147) = 4.2, p = 0.042, η 2 = 0.03). (2) Post-hoc one-way ANOVA comparing groups of same birth-assigned sex for children and adolescents separately with denoting a significant difference between indicated groups (LIFOF, t (147) = 2.7, p = 0.008). (3) Sex (birth-assigned female/male) by Gender (female/male) factorial MANOVA including adolescents only with Tanner stages (pubic hair growth, breast and genital development) as covariates. Here # denotes an interaction effect of Sex and Gender (Body of CC, F (1, 73) = 5.2, p = 0.026, η 2 = 0.07), and ## a main effect of Sex (LCST, F (1, 73) = 7.8, p = 0.032, η 2 = 0.06). All results were considered significant at p < 0.05 and/or η 2 > 0.13, + denotes mean FA per group. C-, child; A-, adolescent; CB, cisgender boy; TG, transgender girl; TB, transgender boy; CG, cisgender girl; L, left; R, right; CST, cortico-spinal tract; CC, corpus callosum; IFOF, inferior fronto-occipital fasciculus; ILF, inferior longitudinal fasciculus; SLF, superior longitudinal fasciculus. For illustrative purposes, Y-axis range is different for a–c and d–f.

Interestingly, a three-way interaction of Pubertal status, Sex and Gender was significant for the left IFOF (LIFOF), F (1, 147) = 7.4, p = 0.007, η 2 = 0.05, right IFOF (RIFOF), F (1, 147) = 4.5, p = 0.036, η2 = 0.03, and forceps major, F (1, 147) = 4.6, p = 0.033, η 2 = 0.03. As displayed in Fig. 2b and 2d, adolescent cisgender individuals had higher FA values than their transgender peers, whereas the opposite pattern -relatively higher FA in trans- v. cisgender was observed in the prepubertal children. Post-hoc one-way ANOVAs with planned contrasts showed significantly higher average FA values in LIFOF in the adolescent cisgender boys than transgender girls, t (147) = 2.7, p = 0.008 (Fig. 2d). This pattern of FA value group differences (adolescent cisgender boys > transgender girls) was not observed in RIFOF and forceps major. No differences were found between the prepubertal cisgender boys and transgender girls, t (147) = −1.2, p = 0.215 (Fig. 2d), thus the difference between the cis- and transgender birth-assigned males was significant only in adolescence. Also, neither the prepubertal, nor adolescent birth-assigned females showed any significant group differences (Fig. 2b + d).

Covarying individual differences in pubertal stage

Tanner stages for pubic hair growth differed significantly among the prepubertal children (see Table 1). Therefore, we conducted an additional Sex by Gender factorial MANOVA among the prepubertal sub-sample, adding Tanner P stages as a covariate. We found an interaction effect across tracts, indicating that transgender children had overall higher FA values than the cisgender boys and girls, ∧ = 0.62, F (13, 55) = 2.6, p = 0.008, η 2 = 0.38, when accounting for Pubertal status. The overall main effects of Sex and Gender were not significant, but had medium effect sizes; η2 = 0.16 and η 2 = 0.14, respectively. Separate univariate ANOVAs confirmed interactions between Sex and Gender in specifically the RIFOF, F (1, 67) = 5.7, p = 0.019, η 2 = 0.08 and LCST, F (1, 67) = 4.3, p = 0.042, η 2 = 0.06. A main effect of Sex was significant for the RSLF, F (1, 67) = 4.9, p = 0.030, η 2 = 0.07, with birth-assigned males having higher FA values than birth-assigned females. There was no significant main effect of Gender for any of the tracts. Post-hoc independent factorial ANOVAs with planned contrasts showed no difference in average FA values for RIFOF or LCST between transgender girls and cisgender boys, or transgender boys and cisgender girls.

Similar as for the children, Tanner stages differed significantly among the adolescent groups. Therefore, we conducted an additional Sex by Gender factorial MANOVA with adolescents only and both Tanner stages (P and M/G) as covariates (these were missing for three transgender girls). This analysis revealed an overall main effect of Sex, ∧ = 0.64, F (13, 61) = 2.7, p = 0.005, η 2 = 0.36, with higher FA values in birth-assigned males than females. No significance, but medium and large effect sizes were found for an overall (across all tracts) main effect of Gender, η 2 = 0.16, and an overall interaction effect of Sex and Gender, η 2 = 0.27, respectively. Separate univariate ANOVAs on the tracts revealed a significant main effect of Sex in left CST, F (1, 73) = 7.8, p = 0.032, η 2 = 0.06. No main effect of Gender was found. However, now an interaction effect of Sex and Gender reached significance in the body of the corpus callosum, F (1, 73) = 5.2, p = 0.026, η 2 = 0.07, indicating that, when accounting for pubertal maturation differences, adolescent cisgender boys and girls had higher FA values than adolescent transgender boys and girls in this tract. Post-hoc independent factorial ANOVAs with planned contrasts showed an FA value difference in the body of the corpus callosum of 0.017, p = 0.031, 95% CI 0.002–0.032 between cisgender girls and transgender boys with higher values in cisgender girls. No difference was found between cisgender boys and transgender girls.

FA in relation to puberty suppression

The adolescent participants with gender incongruence (transgender boys and transgender girls) were the only two groups that had received GnRHa for suppression of endogenous puberty, while the cisgender control groups and the prepubertal children were all treatment-naive. In order to explore whether our findings of relatively lower FA in the adolescent transgender groups might be explained by the GnRHa treatment, we conducted correlation analyses between FA values and the cumulative doses of GnRHa received. These analyses revealed a negative association between FA values and the cumulative doses of GnRHa for the RIFOF; the more GnRHa received, the lower FA values were (r = −0.322, two-sided, uncorrected p = 0.040, N = 41; see Fig. 3). This effect, however, did not survive Bonferroni correction for multiple testing (adjusted α = 0.05/4 tracts tested = 0.0125). For the body of the corpus callosum, the LIFOF, and the forceps major no correlations between FA and the cumulative doses of GnRHa received were found.

Fig. 3. Correlation between of fractional anisotropy (FA) values of the RIFOF and cumulative doses of GnRHa received by the adolescent transgender boys and girls. Data are presented with 95% confidence bands. Correlation analysis including all transgender adolescents revealed a negative association between FA values and the cumulative doses of GnRHa (mg), r = −0.322, two-sided, uncorrected p = 0.040, N = 41. For illustrative purposes, data points for transgender boys and girls are shown in different gray shades.

Discussion

The present study investigated potential sex-atypical (Burke et al., Reference Burke, Manzouri and Savic2017; Kranz et al., Reference Kranz, Hahn, Kaufmann, Küblböck, Hummer, Ganger and Lanzenberger2014; Rametti et al., Reference Rametti, Carrillo, Gomez-Gil, Junque, Segovia, Gomez and Guillamon2011a, Reference Rametti, Carrillo, Gomez-Gil, Junque, Zubiarre-Elorza, Segovia and Guillamon2011b) and transgender-specific (Burke et al., Reference Burke, Manzouri and Savic2017) differences in white-matter microstructure in relation to pubertal status. By using the same analytical approach as Burke et al. (Reference Burke, Manzouri and Savic2017); comparing average FA values in white-matter tracts of interest across groups, the present study aimed to replicate and compare (as much as possible) the current findings in younger samples with those of the prior study in adults. Including both prepubertal and adolescent samples further enabled us to highlight the importance of puberty and adolescence in sex- and gender-specific white-matter microstructure.

In line with several previous studies (Bava et al., Reference Bava, Boucquey, Goldenberg, Thayer, Ward, Jacobus and Tapert2011; Cox et al., Reference Cox, Ritchie, Tucker-Drob, Liewald, Hagenaars, Davies and Deary2016; Den Braber et al., Reference Den Braber, Van't Ent, Stoffers, Linkenkaer-Hansen, Boomsma and De Geus2013; Hsu et al., Reference Hsu, Leemans, Bai, Lee, Tsai, Chiu and Chen2008; Inano et al., Reference Inano, Takao, Hayashi, Abe and Ohtomo2011; Menzler et al., Reference Menzler, Belke, Wehrmann, Krakow, Lengler, Jansen and Knake2011; van Hemmen et al., Reference van Hemmen, Saris, Cohen-Kettenis, Veltman, Pouwels and Bakker2016), we found significant sex effects on FA group differences across age groups, with birth-assigned males showing higher FA values than birth-assigned females in the left CST and right SLF (see Fig. 4 for a summary of all main results). Though not significant for individual tracts, there was an overall significant interaction effect of Sex and Gender, suggesting general differences between trans- and cisgender groups and across both age groups. Interestingly, a significant three-way interaction effect of pubertal status, gender, and sex indicated that specific trans- v. cisgender group differences in FA were dependent on participants' sex and pubertal status; in the body of the corpus callosum both adolescent transgender groups had significantly reduced FA, and in the left IFOF adolescent transgender girls had significantly lower, thus sex-atypical, FA compared with the adolescent cisgender boys. Note however, that effect sizes were small.

Fig. 4. Infographic summarizing all main results (from upper left to lower right side): (1) Interaction effect of Sex and Gender (Body of corpus callosum, F (1, 73) = 5.2, p = 0.026, η 2 = 0.07), (2) three-way interaction effects of Sex, Gender and Pubertal status (L IFOF, F (1, 147) = 7.4, p = 0.007, η 2 = 0.05; R IFOF, F (1, 147) = 4.5, p = 0.036, η 2 = 0.03; forceps major, F (1, 147) = 4.6, p = 0.033, η 2 = 0.03), (3) main effects of Sex (R SLF, F (1, 147) = 4.2, p = 0.042, η 2 = 0.03; L CST, F (1, 147) = 6.1, p = 0.015, η 2 = 0.04), (4) main effects of Pubertal status (L CST, F (1, 147) = 106.3, η 2 = 0.42; R CST, F (1, 147) = 51.9, η 2 = 0.26; Forceps major, F (1, 147) = 150.8, η 2 = 0.51; Forceps minor, F (1, 147) = 183.9, η 2 = 0.56; L IFOF, F (1, 147) = 371.4, η 2 = 0.72; R IFOF, F (1, 147) = 150.3, η 2 = 0.51; L ILF, F (1, 147) = 412.7, η 2 = 0.74; R ILF, F (1, 147) = 136.9, η 2 = 0.48; L SLF, F (1, 147) = 280.7, η 2 = 0.66; R SLF, F (1, 147) = 149.9, η 2 = 0.51; Genu of CC, F (1, 147) = 13.6, η 2 = 0.09; Body of CC, F (1, 147) = 68.4, η 2 = 0.32; Splenium of CC, F (1, 147) = 271.0, η 2 = 0.65. All p < 0.001). FA, fractional anisotropy; cis, cisgender; trans, transgender; L, left, R,  right; CST, cortico-spinal tract; IFOF, inferior fronto-occipital fasciculus; ILF, inferior longitudinal fasciculus; SLF, superior longitudinal fasciculus.

Strikingly, these latter results are highly similar to those of Burke et al. (Reference Burke, Manzouri and Savic2017). In that study, six groups of adult participants were compared; cisgender homosexual and cisgender heterosexual men and women, as well as transgender men and women with diverse sexual orientations (total N = 206). It was found that both the transgender and the cisgender homosexual (reference for both is the sex assigned at birth) groups had sex-atypical average FA values in several white-matter tracts, indicating less pronounced sexual differentiation. Interestingly, when individual differences in sexual orientation were controlled for (by adding scores on the sexual orientation questionnaire as a covariate), significantly lower FA in the right IFOF was specifically found in the transgender women, compared with the cisgender -heterosexual and homosexual- men. Thus, a transgender girl/ woman v. cisgender boy/ man difference in FA was found to be confined to the IFOF, both in the current study and that by Burke et al. (Reference Burke, Manzouri and Savic2017).

The interplay of pubertal status, gender incongruence, and alterations in FA

Interestingly, in the prepubertal sample, we observed higher FA in children with gender incongruence compared with their age-matched cisgender peers. This novel observation is difficult to interpret, due to the lack of comparison literature. Therefore, future longitudinal research investigating how this reversed pattern in childhood can be explained is warranted.

Even though our cross-sectional data limit any conclusions regarding brain development, this study suggests that the years between childhood and mid adolescence, hence early adolescence, represent a highly important period in which puberty-related factors influence white-matter development in both a sex- and gender identity-specific way. Our findings are complementary to previous longitudinal studies in cisgender adolescent samples, which found sex differences in FA to be associated with puberty and increasing gonadal hormone levels (Herting et al., Reference Herting, Maxwell, Irvine and Nagel2012, Reference Herting, Kim, Uban, Kan, Binley and Sowell2017), particularly of testosterone (Ho et al., Reference Ho, Colich, Sisk, Oskirko, Jo and Gotlib2020).

According to clinical treatment protocols (Coleman et al., Reference Coleman, Bockting, Botzer, Cohen-Kettenis, DeCuypere, Feldman and Zucker2012; Hembree et al., Reference Hembree, Cohen-Kettenis, Gooren, Hannema, Meyer, Murad and T'Sjoen2017), puberty suppression treatment is recommended for adolescents who have reached or are beyond the early stages of puberty (Tanner II-III). Thus, our 16-year-old participants had been exposed to endogenous sex hormones for at least some time, before they had started puberty-suppression treatment. Adult participants in the study by Burke et al. (Reference Burke, Manzouri and Savic2017) were treatment-naive, thus they had not received GnRHa and also had been exposed to endogenous sex steroids for several years. Therefore, we speculate that the post-pubescent cis- v. transgender group differences may be due to activational effects, of in particular testosterone. Early pubertal changes in testosterone levels, already before the start of puberty suppression treatment, might thus differently affect white-matter development in trans- v. cisgender youth. Future longitudinal studies should address the question how hormonal changes during puberty affect the development of gender identity and whether (variations in) gender identity, rather than sex per se, might interact with these associations of pubertal and brain development. In particular, the role of testosterone should be examined since this was impossible in the current study, because such data were not available in the transgender groups.

Puberty and puberty suppression in relation to FA

A marked result of the present study was the significant pubertal-status effect in all tracts. Of note, while all adolescents showed higher FA compared to the children, patterns of average FA differences between cisgender and transgender groups reversed across development. More specifically, the cisgender individuals seemed to show a steeper ‘increase’ in FA, resulting in the pattern of adolescent cisgender > transgender group differences.

Suppression of puberty with GnRHa has become the treatment of choice for gender incongruence in youth (Coleman et al., Reference Coleman, Bockting, Botzer, Cohen-Kettenis, DeCuypere, Feldman and Zucker2012; Hembree et al., Reference Hembree, Cohen-Kettenis, Gooren, Hannema, Meyer, Murad and T'Sjoen2017). Its aim is to halt the development of the secondary sex characteristics, and it has been shown to significantly improve adolescents' mental health and well-being (Costa et al., Reference Costa, Dunsford, Skagerberg, Holt, Carmichael and Colizzi2015; van der Miesen, Steensma, de Vries, Bos, & Popma, Reference van der Miesen, Steensma, de Vries, Bos and Popma2020). However, there have been concerns that long-term delay of puberty with GnRHa, and thus prevention of exposure to sex hormones during the early adolescent years could interfere with significant neuro-developmental changes, particularly within the prefrontal cortex, which underlie adolescence-specific changes in behavior (e.g. in behavioral control and social cognition; Chen et al., Reference Chen, Strang, Kolbuck, Rosenthal, Waber, Steinberg and Garofalo2020; Griffin, Clyde, Byng, & Bewley, Reference Griffin, Clyde, Byng and Bewley2020). Both pubertal stage and timing of pubertal onset have been found to influence brain development (Herting & Sowell, Reference Herting and Sowell2017; Juraska & Willing, Reference Juraska and Willing2017). Therefore, the effects of puberty suppression on the brain and cognitive development of youth with gender incongruence should be examined. Indeed, a recent study in mice suggested sex-specific adverse effects of GnRHa on stress-processing, mood and cognition (in females) and locomotion and social behavior (in males; Anacker et al., Reference Anacker, Sydnor, Chen, LaGamma, McGowan, Mastrodonato and Denny2020). Similarly, preliminary evidence from a longitudinal case study suggested adverse effects of GnRHa on the brain and cognition in humans (Schneider et al., Reference Schneider, Spritzer, Soll, Fontanari, Carneiro, Tovar-Moll and Lobato2017). However, in our cross-sectional dataset of transgender adolescents, we did not find significant associations between FA and cumulative doses of GnRHa received. In addition, a study by Staphorsius et al. (Reference Staphorsius, Kreukels, Cohen-Kettenis, Veltman, Burke, Schagen and Bakker2015) showed no effect of GnRHa treatment on executive functioning, measured with the Tower of London task, in 20 transgender adolescents. Systematic, well-powered studies, testing the long-term effects of puberty suppression on the brain and behavior should further investigate these early findings and whether gender-affirming hormone treatment restores potential alterations. Importantly, without puberty suppression, socio-emotional consequences of increased feelings of gender incongruence could also elicit alterations.

The IFOF – neural correlate of gender incongruence?

Relatively lower FA in specifically the IFOF has been linked to gender incongruence in both adolescents (this study) and adults (Burke et al., Reference Burke, Manzouri and Savic2017). In addition, in a longitudinal study of adult transgender men, testosterone treatment was associated with an increase of FA in specifically the IFOF (Burke et al., Reference Burke, Manzouri, Dhejne, Bergstrom, Arver, Feusner and Savic-Berglund2018). How is this particular white-matter tract, in interaction with sex-hormone changes, associated with gender incongruence?

The IFOF (among other tracts) has been suggested to be involved in social-emotional stimuli processing, emotional face recognition, emotion regulation, and attention (Catani & Thiebaut de Schotten, Reference Catani and Thiebaut de Schotten2008; Doricchi, Thiebaut de Schotten, Tomaiuolo, & Bartolomeo, Reference Doricchi, Thiebaut de Schotten, Tomaiuolo and Bartolomeo2008; Philippi, Mehta, Grabowski, Adolphs, & Rudrauf, Reference Philippi, Mehta, Grabowski, Adolphs and Rudrauf2009; Taddei, Tettamanti, Zanoni, Cappa, & Battaglia, Reference Taddei, Tettamanti, Zanoni, Cappa and Battaglia2012). A longitudinal study showed that poor performance during an emotional face perception task at 7–9 years of age, was predictive of reduced FA of this ‘ventral-limbic white-matter pathway’ at age 14–15 years (Taddei et al., Reference Taddei, Tettamanti, Zanoni, Cappa and Battaglia2012). Prior studies have provided preliminary evidence of adult transgender men being less accurate than cisgender females in a visual face processing task (Feusner et al., Reference Feusner, Dervisic, Kosidou, Dhejne, Bookheimer and Savic2016), but could not directly link this behavioral finding to neurobiological group differences.

Several studies have suggested an association between reduced FA in the IFOF and psychiatric conditions, such as generalized anxiety disorder (Liao et al., Reference Liao, Yang, Zhang, He, Su and Li2014), obsessive-compulsive disorder (Garibotto et al., Reference Garibotto, Scifo, Gorini, Alonso, Brambati, Bellodi and Perani2010), and body dysmorphic disorder (Buchanan et al., Reference Buchanan, Rossell, Maller, Toh, Brennan and Castle2013). Furthermore, lower FA in the IFOF has been linked to non-clinical anxious personality traits (Lu, Yang, Chu, & Wu, Reference Lu, Yang, Chu and Wu2018) and was recently proposed to reflect a more ‘general psychopathology marker’ (Riem et al., Reference Riem, van Hoof, Garrett, Rombouts, van der Wee, van IJzendoorn and Vermeiren2019). Important to note, gender incongruence is not pathological. However, experiencing gender incongruence may come with disadvantages leading to an increased risk of mental health problems. These include, among others, minority stress, societal inequities, and barriers to healthcare, e.g., due to long waiting lists for transgender-specific healthcare, lack of physicians' knowledge, or discrimination in healthcare encounters (Braun, Garcia-Grossman, Quinones-Rivera, & Deutsch, Reference Braun, Garcia-Grossman, Quinones-Rivera and Deutsch2017; Koehler, Strauss, Briken, Szuecs, & Nieder, Reference Koehler, Strauss, Briken, Szuecs and Nieder2021; Lo & Horton, Reference Lo and Horton2016). In line with this, gender diversity in the general population has been associated with adolescent psychopathology (Burke, Reference Burke2020; Potter et al., Reference Potter, Dube, Allgaier, Loso, Ivanova, Barrios and Johns2020) and young individuals with gender incongruence show elevated rates of diverse mental health problems and psychiatric comorbidity, especially before the start of treatment (Aitken, VanderLaan, Wasserman, Stojanovski, & Zucker, Reference Aitken, VanderLaan, Wasserman, Stojanovski and Zucker2016; de Vries, Doreleijers, Steensma, & Cohen-Kettenis, Reference de Vries, Doreleijers, Steensma and Cohen-Kettenis2011; Griffin et al., Reference Griffin, Clyde, Byng and Bewley2020; Holt, Skagerberg, & Dunsford, Reference Holt, Skagerberg and Dunsford2016; Kaltiala-Heino, Sumia, Työläjärvi, & Lindberg, Reference Kaltiala-Heino, Sumia, Työläjärvi and Lindberg2015).

Thus, brain structural alterations in the IFOF seem to be a common neurobiological denominator of (vulnerability toward) psychopathology and sex-gender incongruence. Future longitudinal studies should further investigate which neurobiological, psycho-developmental, and societal context-related factors are predictive of adolescent mental health problems, also gender incongruence.

Strengths and limitations

A strength of the present study is the inclusion of the unique sample of prepubertal children and adolescents with gender incongruence and the hypothesis-driven analysis approach. However, because of the relatively small sample sizes and effect sizes in some analyses, generalizability of results may be limited. Also, our cross-sectional design prohibits any conclusions regarding causality. Therefore, cautious interpretation and longitudinal replication of these findings are warranted. In addition, when averaging FA values, we did not apply masking, therefore, it is not certain that only white matter was taken into account during this process. Lastly, all FA results in frontal areas might have been influenced by the lack of top up and down epi-distortion correction.

Conclusion

Taken together, in the present study we replicated the finding of lower FA in the IFOF of post-pubescent transgender girls and women, which suggests this to be a salient neural correlate of gender incongruence. In addition, we demonstrate that these adolescence-specific trans- v. cisgender group differences in FA show the reverse pattern in childhood. This highlights the complexity with which sex hormones, during different phases of human development, interact with and impact psychological and brain development, including the gendered perception of self. Our findings add important insights into the neurobiological substrate associated with gender incongruence.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0033291721005547.

Footnotes

† The notes appear after the main text.

1 Diffusion tensor imaging data acquisition was scheduled at the end of the scanning protocol and the MR session already exceeded the time allotted.

References

Aitken, M., VanderLaan, D. P., Wasserman, L., Stojanovski, S., & Zucker, K. J. (2016). Self-harm and suicidality in children referred for gender dysphoria. Journal of the American Academy of Child and Adolescent Psychiatry, 55, 513–520. doi: 10.1016/j.jaac.2016.04.001CrossRefGoogle ScholarPubMed
Anacker, C., Sydnor, E., Chen, B. K., LaGamma, C. C., McGowan, J. C., Mastrodonato, A., & …Denny, C. A. (2020). Behavioral and neurobiological effects of GnRH agonist treatment in mice—potential implications for puberty suppression in transgender individuals. Neuropsychopharmacology, 46, 882–890. doi: 10.1038/s41386-020-00826-1CrossRefGoogle ScholarPubMed
Bava, S., Boucquey, V., Goldenberg, D., Thayer, R. E., Ward, M., Jacobus, J., & Tapert, S. F. (2011). Sex differences in adolescent white matter architecture. Brain Research, 1375, 41–48. doi: 10.1016/j.brainres.2010.12.051CrossRefGoogle ScholarPubMed
Braun, H. M., Garcia-Grossman, I. R., Quinones-Rivera, A., & Deutsch, M. B. (2017). Outcome and impact evaluation of a transgender health course for health profession students. LGBT Health, 4(1), 55–61. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/28075699. doi:10.1089/lgbt.2016.0119.CrossRefGoogle ScholarPubMed
Buchanan, B. G., Rossell, S. L., Maller, J. J., Toh, W. L., Brennan, S., & Castle, D. J. (2013). Brain connectivity in body dysmorphic disorder compared with controls: A diffusion tensor imaging study. Psychological Medicine, 43, 2513–2521. doi: 10.1017/S0033291713000421CrossRefGoogle ScholarPubMed
Burke, S. M. (2020). Commentary: Gender diversity and adolescent mental health – a reflection on potter et al. 2020. Journal of Child Psychology and Psychiatry, 62, 180–183. doi: 10.1111/JCPP.13309CrossRefGoogle Scholar
Burke, S. M., Cohen-Kettenis, P. T., Veltman, D. J., Klink, D. T., & Bakker, J. (2014). Hypothalamic response to the chemo-signal androstadienone in gender dysphoric children and adolescents. Frontiers in Endocrinology, 5, 1–10. doi: 10.3389/fendo.2014.00060CrossRefGoogle Scholar
Burke, S. M., Manzouri, A. H., Dhejne, C., Bergstrom, K., Arver, S., Feusner, J. D., & Savic-Berglund, I. (2018). Testosterone effects on the brain in transgender Men. Cerebral Cortex, 28, 1582–1596. doi: 10.1093/cercor/bhx054CrossRefGoogle ScholarPubMed
Burke, S. M., Manzouri, A. H., & Savic, I. (2017). Structural connections in the brain in relation to gender identity and sexual orientation. Scientific Reports, 7, 17954. doi: 10.1038/s41598-017-17352-8CrossRefGoogle ScholarPubMed
Catani, M. (2006). Diffusion tensor magnetic resonance imaging tractography in cognitive disorders. Current Opinion in Neurology, 19, 599–606. doi: 10.1097/01.wco.0000247610.44106.3fCrossRefGoogle ScholarPubMed
Catani, M. (2007). From hodology to function. Brain, 130, 602–605. doi: 10.1093/brain/awm008CrossRefGoogle ScholarPubMed
Catani, M., & Thiebaut de Schotten, M. (2008). A diffusion tensor imaging tractography atlas for virtual in vivo dissections. Cortex; A Journal Devoted to The Study of the Nervous System and Behavior, 44, 1105–1132. doi: 10.1016/j.cortex.2008.05.004CrossRefGoogle ScholarPubMed
Chahal, R., Vilgis, V., Grimm, K. J., Hipwell, A. E., Forbes, E. E., Keenan, K., & Guyer, A. E. (2018). Girls’ pubertal development is associated with white matter microstructure in late adolescence. Neuroimage, 181, 659–669. doi: 10.1016/J.NEUROIMAGE.2018.07.050CrossRefGoogle ScholarPubMed
Chen, D., Strang, J. F., Kolbuck, V. D., Rosenthal, S. M., Waber, D. P., Steinberg, L., & … Garofalo, R. (2020). Consensus parameter: Research methodologies to evaluate neurodevelopmental effects of pubertal suppression in transgender youth. Transgender Health, 5, 246–257.CrossRefGoogle ScholarPubMed
Coleman, E., Bockting, W., Botzer, M., Cohen-Kettenis, P., DeCuypere, G., Feldman, J., & … Zucker, K. (2012). Standards of care for the health of transsexual, transgender, and gender-nonconforming people, version 7. International Journal of Transgenderism, 13, 165–232. doi: 10.1080/15532739.2011.700873CrossRefGoogle Scholar
Costa, R., Dunsford, M., Skagerberg, E., Holt, V., Carmichael, P., & Colizzi, M. (2015). Psychological support, puberty suppression, and psychosocial functioning in adolescents with gender dysphoria. The Journal of Sexual Medicine, 12, 2206–2214. doi: 10.1111/jsm.13034CrossRefGoogle ScholarPubMed
Cox, S. R., Ritchie, S. J., Tucker-Drob, E. M., Liewald, D. C., Hagenaars, S. P., Davies, G., & … Deary, I. J. (2016). Ageing and brain white matter structure in 3513 UK biobank participants. Nature Communications, 7, 1–13. doi: 10.1038/ncomms13629CrossRefGoogle Scholar
Den Braber, A., Van't Ent, D., Stoffers, D., Linkenkaer-Hansen, K., Boomsma, D. I., & De Geus, E. J. C. (2013). Sex differences in gray and white matter structure in age-matched unrelated males and females and opposite-sex siblings. International Journal of Psychological Research, 6, 7–21. doi: 10.21500/20112084.712CrossRefGoogle Scholar
de Vries, A. L. C., Doreleijers, T. A. H., Steensma, T. D., & Cohen-Kettenis, P. T. (2011). Psychiatric comorbidity in gender dysphoric adolescents. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 52, 1195–1202. doi: 10.1111/j.1469-7610.2011.02426.xCrossRefGoogle ScholarPubMed
Doricchi, F., Thiebaut de Schotten, M., Tomaiuolo, F., & Bartolomeo, P. (2008). White matter (dis)connections and gray matter (dys)functions in visual neglect: Gaining insights into the brain networks of spatial awareness. Cortex, 44, 983–995. doi: 10.1016/j.cortex.2008.03.006CrossRefGoogle ScholarPubMed
Dörner, G. (1988). Neuroendocrine response to estrogen and brain differentiation in heterosexuals, homosexuals, and transsexuals. Archives of Sexual Behavior, 17, 57–75.CrossRefGoogle ScholarPubMed
Fausto-Sterling, A. (2019). Gender/Sex, sexual orientation, and identity are in the body: How did they Get there? Journal of Sex Research, 56, 529–555. doi: 10.1080/00224499.2019.1581883CrossRefGoogle Scholar
Feusner, J. D., Dervisic, J., Kosidou, K., Dhejne, C., Bookheimer, S., & Savic, I. (2016). Female-to-Male transsexual individuals demonstrate different Own body identification. Archives of Sexual Behavior, 45, 525–536. doi: 10.1007/s10508-015-0596-zCrossRefGoogle ScholarPubMed
Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). London: Sage.Google Scholar
Garibotto, V., Scifo, P., Gorini, A., Alonso, C. R., Brambati, S., Bellodi, L., & Perani, D. (2010). Disorganization of anatomical connectivity in obsessive-compulsive disorder: A multi-parameter diffusion tensor imaging study in a subpopulation of patients. Neurobiology of Disease, 37, 468–476. doi: 10.1016/j.nbd.2009.11.003CrossRefGoogle Scholar
Genc, S., Seal, M. L., Dhollander, T., Malpas, C. B., Hazell, P., & Silk, T. J. (2017). White matter alterations at pubertal onset. Neuroimage, 156, 286–292. doi: 10.1016/j.neuroimage.2017.05.017CrossRefGoogle ScholarPubMed
Griffin, L., Clyde, K., Byng, R., & Bewley, S. (2020). Sex, gender and gender identity: A re-evaluation of the evidence. BJPsych Bulletin, 45, 1–9. doi: 10.1192/bjb.2020.73Google Scholar
Guillamon, A., Junque, C., & Gómez-Gil, E. (2016). A review of the status of brain structure research in transsexualism. Archives of Sexual Behavior, 45, 1615–1648. doi: 10.1007/s10508-016-0768-5CrossRefGoogle ScholarPubMed
Halim, M. L., & Ruble, D. (2010). Gender identity and stereotyping in early and middle childhood. New York: Springer, pp. 495–525.Google Scholar
Hembree, W. C., Cohen-Kettenis, P. T., Gooren, L., Hannema, S. E., Meyer, W. J., Murad, M. H., & … T'Sjoen, G. G. (2017). Endocrine treatment of gender-dysphoric/ gender-incongruent persons: An endocrine society × clinical practice guideline. Journal of Clinical Endocrinology and Metabolism, 102, 3869–3903. doi: 10.1210/jc.2017-01658CrossRefGoogle ScholarPubMed
Herting, M. M., Kim, R., Uban, K. A., Kan, E., Binley, A., & Sowell, E. R. (2017). Longitudinal changes in pubertal maturation and white matter microstructure. Psychoneuroendocrinology, 81, 70–79. doi: 10.1016/j.psyneuen.2017.03.017CrossRefGoogle ScholarPubMed
Herting, M. M., Maxwell, E. C., Irvine, C., & Nagel, B. J. (2012). The impact of sex, puberty, and hormones on white matter microstructure in adolescents. Cerebral Cortex, 22, 1979–1992. doi: 10.1093/cercor/bhr246CrossRefGoogle ScholarPubMed
Herting, M. M., & Sowell, E. R. (2017). Puberty and structural brain development in humans. Frontiers in Neuroendocrinology, 44, 122–137. doi: 10.1016/j.yfrne.2016.12.003CrossRefGoogle ScholarPubMed
Ho, T. C., Colich, N. L., Sisk, L. M., Oskirko, K., Jo, B., & Gotlib, I. H. (2020). Sex differences in the effects of gonadal hormones on white matter microstructure development in adolescence. Developmental Cognitive Neuroscience, 42, 100773. doi: 10.1016/j.dcn.2020.100773CrossRefGoogle ScholarPubMed
Holt, V., Skagerberg, E., & Dunsford, M. (2016). Young people with features of gender dysphoria: Demographics and associated difficulties. Clinical Child Psychology and Psychiatry, 21, 108–118. doi: 10.1177/1359104514558431CrossRefGoogle ScholarPubMed
Hsu, J.-L. L., Leemans, A., Bai, C.-H. H., Lee, C.-H. H., Tsai, Y.-F. F., Chiu, H.-C. C., & Chen, W.-H. H. (2008). Gender differences and age-related white matter changes of the human brain: A diffusion tensor imaging study. NeuroImage, 39, 566–577. doi: 10.1016/j.neuroimage.2007.09.017CrossRefGoogle Scholar
Inano, S., Takao, H., Hayashi, N., Abe, O., & Ohtomo, K. (2011). Effects of Age and gender on white matter integrity. American Journal of Neuroradiology, 32, 2103–2109.CrossRefGoogle ScholarPubMed
Juraska, J. M., & Willing, J. (2017). Pubertal onset as a critical transition for neural development and cognition. Brain Research, 1654, 87–94. doi: 10.1016/j.brainres.2016.04.012CrossRefGoogle ScholarPubMed
Kaltiala-Heino, R., Sumia, M., Työläjärvi, M., & Lindberg, N. (2015). Two years of gender identity service for minors: Overrepresentation of natal girls with severe problems in adolescent development. Child and Adolescent Psychiatry and Mental Health, 9, 9. doi: 10.1186/s13034-015-0042-yCrossRefGoogle ScholarPubMed
Kochunov, P., Jahanshad, N., Marcus, D., Winkler, A., Sprooten, E., Nichols, T. E., & … Van Essen, D. C. (2015). Heritability of fractional anisotropy in human white matter: A comparison of human connectome project and ENIGMA-DTI data. Neuroimage, 111, 300–311. doi: 10.1016/j.neuroimage.2015.02.050CrossRefGoogle ScholarPubMed
Koehler, A., Strauss, B., Briken, P., Szuecs, D., & Nieder, T. O. (2021). Centralized and decentralized delivery of transgender health care services: A systematic review and a global expert survey in 39 countries. Front Endocrinol (Lausanne), 12, 717914. doi: 10.3389/fendo.2021.717914, Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/34630327.CrossRefGoogle Scholar
Kranz, G. S., Hahn, A., Kaufmann, U., Küblböck, M., Hummer, A., Ganger, S., & … Lanzenberger, R. (2014). White matter microstructure in transsexuals and controls investigated by diffusion tensor imaging. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 34, 15466–15475. doi: 10.1523/JNEUROSCI.2488-14.2014CrossRefGoogle ScholarPubMed
Kreukels, B. P. C., & Cohen-Kettenis, P. T. (2011). Puberty suppression in gender identity disorder: The Amsterdam experience. Nature Reviews, Endocrinology, 7, 466–472. doi: 10.1038/nrendo.2011.78CrossRefGoogle ScholarPubMed
Kreukels, B. P. C., & Guillamon, A. (2016). Neuroimaging studies in people with gender incongruence. International Review of Psychiatry, 28, 120–128. doi: 10.3109/09540261.2015.1113163CrossRefGoogle ScholarPubMed
Liao, M., Yang, F., Zhang, Y., He, Z., Su, L., & Li, L. (2014). White matter abnormalities in adolescents with generalized anxiety disorder: A diffusion tensor imaging study. BMC Psychiatry, 14, 41. doi: 10.1186/1471-244X-14-41CrossRefGoogle ScholarPubMed
Lo, S., & Horton, R. (2016). Transgender health: An opportunity for global health equity. Lancet, 388(10042), 316–318. doi: 10.1016/S0140-6736(16)30675-4, Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/27323923.CrossRefGoogle ScholarPubMed
Lu, M., Yang, C., Chu, T., & Wu, S. (2018). Cerebral white matter changes in young healthy individuals with high trait anxiety: A tract-based spatial statistics study. Frontiers in Neurology, 9, 1–8. doi: 10.3389/fneur.2018.00704CrossRefGoogle ScholarPubMed
Manzouri, A. H., & Savic, I. (2019). Possible neurobiological underpinnings of homosexuality and gender dysphoria. Cerebral Cortex, 29, 2084–2101. doi: 10.1093/cercor/bhy090CrossRefGoogle ScholarPubMed
Marshall, W. A., & Tanner, J. M. (1969). Variations in pattern of pubertal changes in girls. Archives of Disease in Childhood, 44, 291–303. doi: 10.1136/adc.44.235.291CrossRefGoogle ScholarPubMed
Marshall, W. A., & Tanner, J. M. (1970). Variations in the pattern of pubertal changes in boys. Archives of Disease in Children, 45, 13–23. doi: 10.1136/adc.45.239.13CrossRefGoogle ScholarPubMed
Menzler, K., Belke, M., Wehrmann, E., Krakow, K., Lengler, U., Jansen, A., & … Knake, S. (2011). Men and women are different: Diffusion tensor imaging reveals sexual dimorphism in the microstructure of the thalamus, corpus callosum and cingulum. Neuroimage, 54, 2557–2562. doi: 10.1016/j.neuroimage.2010.11.029CrossRefGoogle ScholarPubMed
Mori, S., Wakana, S., Nagae-Poetsche, L. M., & van Zijl, P. C. M. (2005). MRI Atlas of Human White Matter (1st ed.). Amsterdam: Elsevier.Google Scholar
Nguyen, H. B., Loughead, J., Lipner, E., Hantsoo, L., Kornfield, S. L., & Epperson, C. N. (2019). What has sex got to do with it? The role of hormones in the transgender brain. Neuropsychopharmacology, 44, 22–37. doi: 10.1038/s41386-018-0140-7CrossRefGoogle Scholar
Nota, N. M., Kreukels, B. P. C., den Heijer, M., Veltman, D. J., Cohen-Kettenis, P. T., Burke, S. M., & Bakker, J. (2017). Brain functional connectivity patterns in children and adolescents with gender dysphoria: Sex-atypical or not? Psychoneuroendocrinology, 86, 187–195. doi: 10.1016/j.psyneuen.2017.09.014CrossRefGoogle ScholarPubMed
Pang, K. C., de Graaf, N. M., Chew, D., Hoq, M., Keith, D. R., Carmichael, P., & Steensma, T. D. (2020). Association of media coverage of transgender and gender diverse issues with rates of referral of transgender children and adolescents to specialist gender clinics in the UK and Australia. JAMA Network Open, 3, 1–10. doi: 10.1001/jamanetworkopen.2020.11161CrossRefGoogle ScholarPubMed
Pangelinan, M. M., Leonard, G., Perron, M., Pike, G. B., Richer, L., Veillette, S., & … Paus, T. (2016). Puberty and testosterone shape the corticospinal tract during male adolescence. Brain Structure and Function, 221, 1083–1094. doi: 10.1007/s00429-014-0956-9CrossRefGoogle ScholarPubMed
Peper, J. S., de Reus, M. A., van den Heuvel, M. P., & Schutter, D. J. L. G. (2015). Short fused? Associations between white matter connections, sex steroids, and aggression across adolescence. Human brain mapping, 36, 1043–1052. doi: 10.1002/hbm.22684CrossRefGoogle ScholarPubMed
Peper, J. S., Mandl, R. C. W., Braams, B. R., de Water, E., Heijboer, A. C., Koolschijn, P. C. M. P., & Crone, E. A. (2013). Delay discounting and frontostriatal fiber tracts: A combined DTI and MTR study on impulsive choices in healthy young adults. Cerebral Cortex, 23, 1695–1702. doi: 10.1093/cercor/bhs163CrossRefGoogle Scholar
Philippi, C. L., Mehta, S., Grabowski, T., Adolphs, R., & Rudrauf, D. (2009). Damage to association fiber tracts impairs recognition of the facial expression of emotion. Journal of Neuroscience, 29, 15089–15099. doi: 10.1523/JNEUROSCI.0796-09.2009CrossRefGoogle ScholarPubMed
Potter, A., Dube, S., Allgaier, N., Loso, H., Ivanova, M., Barrios, L. C., & … Johns, M. M. (2020). Early adolescent gender diversity and mental health in the adolescent brain cognitive development study. Journal of Child Psychology and Psychiatry, 62, 171–179. doi: 10.1111/jcpp.13248CrossRefGoogle ScholarPubMed
Rametti, G., Carrillo, B., Gomez-Gil, E., Junque, C., Segovia, S., Gomez, A., & Guillamon, A. (2011a). White matter microstructure in female to male transsexuals before cross-sex hormonal treatment. A diffusion tensor imaging study. Journal of Psychiatric Research, 45, 199–204. doi: 10.1016/j.jpsychires.2010.05.006CrossRefGoogle ScholarPubMed
Rametti, G., Carrillo, B., Gomez-Gil, E., Junque, C., Zubiarre-Elorza, L., Segovia, S., & … Guillamon, A. (2011b). The microstructure of white matter in male to female transsexuals before cross-sex hormonal treatment. A DTI study. Journal of Psychiatric Research, 45, 949–954. doi: 10.1016/j.jpsychires.2010.11.007CrossRefGoogle ScholarPubMed
Riem, M. M. E., van Hoof, M. J., Garrett, A. S., Rombouts, S. A. R. B., van der Wee, N. J. A., van IJzendoorn, M. H., & Vermeiren, R. R. J. M. (2019). General psychopathology factor and unresolved-disorganized attachment uniquely correlated to white matter integrity using diffusion tensor imaging. Behavioural Brain Research, 359, 1–8. doi: 10.1016/j.bbr.2018.10.014CrossRefGoogle ScholarPubMed
Ruble, D. N., Martin, C. L., & Berenbaum, S. A. (2006). Gender development. John Wiley & Sons Inc., pp. 858–932.Google Scholar
Schmithorst, V. J., Holland, S. K., & Dardzinski, B. J. (2008). Developmental differences in white matter architecture between boys and girls. Human Brain Mapping, 29, 696–710. doi: 10.1002/hbm.20431CrossRefGoogle ScholarPubMed
Schneider, M. A., Spritzer, P. M., Soll, B. M. B., Fontanari, A. M. V., Carneiro, M., Tovar-Moll, F., & … Lobato, M. I. R. (2017). Brain maturation, cognition and voice pattern in a gender dysphoria case under pubertal suppression. Frontiers in Human Neuroscience, 11, 1–9. doi: 10.3389/fnhum.2017.00528CrossRefGoogle Scholar
Staphorsius, A. S., Kreukels, B. P., Cohen-Kettenis, P. T., Veltman, D. J., Burke, S. M., Schagen, S. E., & … Bakker, J. (2015). Puberty suppression and executive functioning: An fMRI-study in adolescents with gender dysphoria. Psychoneuroendocrinology, 56, 190–199. doi: 10.1016/j.psyneuen.2015.03.007CrossRefGoogle ScholarPubMed
Swaab, D. F., & Hofman, M. A. (1995). Sexual differentiation of the human hypothalamus in relation to gender and sexual orientation. Trends in Neurosciences, 18, 264–270. doi: 10.1016/0166-2236(95)80007-OCrossRefGoogle ScholarPubMed
Taddei, M., Tettamanti, M., Zanoni, A., Cappa, S., & Battaglia, M. (2012). Brain white matter organisation in adolescence is related to childhood cerebral responses to facial expressions and harm avoidance. Neuroimage, 61, 1394–1401. doi: 10.1016/j.neuroimage.2012.03.062CrossRefGoogle ScholarPubMed
Uribe, C., Junque, C., Gómez-Gil, E., Abos, A., Mueller, S. C., & Guillamon, A. (2020). Brain network interactions in transgender individuals with gender incongruence. Neuroimage, 211, 116613. doi: 10.1016/j.neuroimage.2020.116613CrossRefGoogle ScholarPubMed
van der Miesen, A. I. R., Steensma, T. D., de Vries, A. L. C., Bos, H., & Popma, A. (2020). Psychological functioning in transgender adolescents before and after gender-affirmative care compared with cisgender general population peers. Journal of Adolescent Health, 66, 699–704. doi: 10.1016/j.jadohealth.2019.12.018CrossRefGoogle ScholarPubMed
van Hemmen, J., Saris, I. M. J., Cohen-Kettenis, P. T., Veltman, D. J., Pouwels, P. J. W., & Bakker, J. (2016). Sex differences in white matter microstructure in the human brain predominantly reflect differences in sex hormone exposure. Cerebral Cortex, 27, 2994–3001. doi: 10.1093/cercor/bhw156Google Scholar
World Health Organization (2018). International classification of diseases. WHO.Google Scholar
Zhou, J.-N., Hofman, M. A., Gooren, L. J. G., & Swaab, D. F. (1995). A sex difference in the human brain and its relation to transsexuality. Nature, 378, 68–70. doi: 10.1038/378068a0CrossRefGoogle ScholarPubMed
Zucker, K. J. (2019). Adolescents with gender dysphoria: Reflections on some contemporary clinical and research issues. Archives of Sexual Behavior, 48, 1983–1992. doi: 10.1007/s10508-019-01518-8CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Anatomical representation of the Inferior Frontal Occipital Fasciculus in (a) sagittal and (b) transverse radiological display orientation. The bilateral IFOF was selected from the JHU white-matter tractography atlas (Mori, Wakana, van Zijl, & Nagae-Poetscher, 2005) and overlayed on the FMRIB58_FA_1 mm standard space image. The figure was created using FSL image viewer FSLeyes.

Figure 1

Table 1. Subject characteristics per group

Figure 2

Fig. 2. Boxplots showing fractional anisotropy (FA) values per tract (a–f). Group differences were analyzed with: (1) Sex (birth-assigned female/male) by Gender identity (female/male) by Pubertal status (prepubertal/adolescent) factorial MANOVA including all cisgender and transgender groups without covariates. Here * denotes significant three-way interaction effects of Sex, Gender and Pubertal status (LIFOF, F (1, 147) = 7.4, p = 0.007, η2 = 0.05; RIFOF, F (1, 147) = 4.5, p = 0.036, η2 = 0.03; forceps major, F (1, 147) = 4.6, p = 0.033, η2 = 0.03), ** main effects of Pubertal status (LCST, F (1, 147) = 106.3, η2 = 0.42; RCST, F (1, 147) = 51.9, η2 = 0.26; Forceps major, F (1, 147) = 150.8, η2 = 0.51; Forceps minor, F (1, 147) = 183.9, η2 = 0.56; LIFOF, F (1, 147) = 371.4, η2 = 0.72; RIFOF, F (1, 147) = 150.3, η2 = 0.51; LILF, F (1, 147) = 412.7, η2 = 0.74; RILF, F (1, 147) = 136.9, η2 = 0.48; LSLF, F (1, 147) = 280.7, η2 = 0.66; RSLF, F (1, 147) = 149.9, η2 = 0.51; Genu of CC, F (1, 147) = 13.6, η2 = 0.09; Body of CC, F (1, 147) = 68.4, η2 = 0.32; Splenium of CC, F (1, 147) = 271.0, η2 = 0.65. All p < 0.001), and *** main effects of Sex (LCST, F (1, 147) = 6.1, p = 0.015, η2 = 0.04; RSLF, F (1, 147) = 4.2, p = 0.042, η2 = 0.03). (2) Post-hoc one-way ANOVA comparing groups of same birth-assigned sex for children and adolescents separately with denoting a significant difference between indicated groups (LIFOF, t (147) = 2.7, p = 0.008). (3) Sex (birth-assigned female/male) by Gender (female/male) factorial MANOVA including adolescents only with Tanner stages (pubic hair growth, breast and genital development) as covariates. Here # denotes an interaction effect of Sex and Gender (Body of CC, F (1, 73) = 5.2, p = 0.026, η2 = 0.07), and ## a main effect of Sex (LCST, F (1, 73) = 7.8, p = 0.032, η2 = 0.06). All results were considered significant at p < 0.05 and/or η2 > 0.13, + denotes mean FA per group. C-, child; A-, adolescent; CB, cisgender boy; TG, transgender girl; TB, transgender boy; CG, cisgender girl; L, left; R, right; CST, cortico-spinal tract; CC, corpus callosum; IFOF, inferior fronto-occipital fasciculus; ILF, inferior longitudinal fasciculus; SLF, superior longitudinal fasciculus. For illustrative purposes, Y-axis range is different for a–c and d–f.

Figure 3

Fig. 3. Correlation between of fractional anisotropy (FA) values of the RIFOF and cumulative doses of GnRHa received by the adolescent transgender boys and girls. Data are presented with 95% confidence bands. Correlation analysis including all transgender adolescents revealed a negative association between FA values and the cumulative doses of GnRHa (mg), r = −0.322, two-sided, uncorrected p = 0.040, N = 41. For illustrative purposes, data points for transgender boys and girls are shown in different gray shades.

Figure 4

Fig. 4. Infographic summarizing all main results (from upper left to lower right side): (1) Interaction effect of Sex and Gender (Body of corpus callosum, F (1, 73) = 5.2, p = 0.026, η2 = 0.07), (2) three-way interaction effects of Sex, Gender and Pubertal status (L IFOF, F (1, 147) = 7.4, p = 0.007, η2 = 0.05; R IFOF, F (1, 147) = 4.5, p = 0.036, η2 = 0.03; forceps major, F (1, 147) = 4.6, p = 0.033, η2 = 0.03), (3) main effects of Sex (R SLF, F (1, 147) = 4.2, p = 0.042, η2 = 0.03; L CST, F (1, 147) = 6.1, p = 0.015, η2 = 0.04), (4) main effects of Pubertal status (L CST, F (1, 147) = 106.3, η2 = 0.42; R CST, F (1, 147) = 51.9, η2 = 0.26; Forceps major, F (1, 147) = 150.8, η2 = 0.51; Forceps minor, F (1, 147) = 183.9, η2 = 0.56; L IFOF, F (1, 147) = 371.4, η2 = 0.72; R IFOF, F (1, 147) = 150.3, η2 = 0.51; L ILF, F (1, 147) = 412.7, η2 = 0.74; R ILF, F (1, 147) = 136.9, η2 = 0.48; L SLF, F (1, 147) = 280.7, η2 = 0.66; R SLF, F (1, 147) = 149.9, η2 = 0.51; Genu of CC, F (1, 147) = 13.6, η2 = 0.09; Body of CC, F (1, 147) = 68.4, η2 = 0.32; Splenium of CC, F (1, 147) = 271.0, η2 = 0.65. All p < 0.001). FA, fractional anisotropy; cis, cisgender; trans, transgender; L, left, R,  right; CST, cortico-spinal tract; IFOF, inferior fronto-occipital fasciculus; ILF, inferior longitudinal fasciculus; SLF, superior longitudinal fasciculus.

Supplementary material: File

van Heesewijk et al. supplementary material

van Heesewijk et al. supplementary material

Download van Heesewijk et al. supplementary material(File)
File 37.7 KB