Replication of Previous Findings? Comparing Gray Matter Volumes in Transgender Individuals with Gender Incongruence and Cisgender Individuals

Clemens, Benjamin; Votinov, Mikhail; Puiu, Andrei A.; Schüppen, André; Hüpen, Philippa; Neulen, J.; Derntl, Birgit; Habel, Ute

doi:10.3390/jcm10071454

Cited by 7 publications

(11 citation statements)

References 62 publications

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“…Additionally, in line with a previous study [5] and to avoid overfitting due to the large number of whole-brain voxelwise GMV features, we reduced the dimensionality of the feature set by applying Principal Component Analysis (PCA) before training the structural sex classifier, leading to a reduced spatial interpretability. Future studies could complement the present findings by employing different approaches to dimensionality reduction, for example by using parcel-wise rather than voxel-wise data extraction as used in previous studies [37]. Such an approach would make it possible to determine which brain regions best classify females and males.…”

Section: Discussionmentioning

confidence: 80%

Section: Discussionmentioning

confidence: 99%

“…While featurewise TIV confound removal produced unbiased models it resulted in a much lower accuracy. Further, we applied the cisgender trained models to transgender individuals, which – according to some reports [5, 33, 34, 37, 38] – differ in local and global brain size [38]. Previous studies have suggested that differences in performance of sex classification models on cisgender and transgender samples might indicate qualitative differences in structural brain organization between cisgender and transgender brains and thus for a modulation of brain structure by the interaction of sex and gender identity [5, 6].…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies employing group comparisons reported structural alterations for TW in comparison to CM in regions as e.g. putamen, insula, hypothalamus and ventricles as well as altered white matter connectivity [5, 34, 35, 37, 38, 53]. These changes might be related to plasticity of the brain following sex reassignment and CHT for transgender individuals following the desire to resemble the experienced gender identity also physically, which has been reported to cause a development of transgender brains towards brain volumetric proportions that align with their gender identity [38, 54].…”

Section: Discussionmentioning

confidence: 99%

“…For example, some studies comparing groups of cisgender and transgender individuals have described regional differences in grey matter volume (GMV) in the putamen [37] and insula [5]. Additionally, transgender individuals undergoing cross-sex hormone treatment (CHT) were reported to show structural alterations in the hypothalamus and the third ventricle [38].…”

Section: Introductionmentioning

confidence: 99%

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Accurate sex prediction of cisgender and transgender individuals without brain size bias

Lisa

Hamdan

Hoffstaedter

et al. 2022

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Brain size differs substantially between human males and females. This difference in total intracranial volume (TIV) can cause bias when employing machine-learning approaches for the investigation of sex differences in brain morphology. TIV-biased models will likely not capture actual qualitative sex differences in brain organization but rather learn to classify an individual's sex based on brain size differences, thus leading to spurious and misleading conclusions, for example when comparing brain morphology between cisgender- and transgender individuals. Here, TIV bias in sex classification models applied to cis- and transgender individuals was systematically investigated by controlling for brain size either through featurewise confound removal or by matching training samples for TIV. Our results provide evidence that non-TIV-biased models can classify the sex of both cis- and transgender individuals with high accuracy, highlighting the importance of appropriate modelling to avoid bias in automated decision making.

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Section: Discussionmentioning

confidence: 80%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Accurate sex prediction of cisgender and transgender individuals without brain size bias

Lisa

Hamdan

Hoffstaedter

et al. 2022

Preprint

Self Cite

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Gender Diversity and Brain Morphology Among Adolescents

et al. 2023

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ImportanceGender-diverse youths have higher rates of mental health problems compared with the general population, as shown in both clinical and nonclinical populations. Brain correlates of gender diversity, however, have been reported only among youths with gender dysphoria or in transgender individuals.ObjectiveTo examine brain morphologic correlates of gender diversity among adolescents from a general pediatric population who were assigned male or female at birth, separately.Design, Setting, and ParticipantsThis cross-sectional study was embedded in Generation R, a multiethnic population-based study conducted in Rotterdam, the Netherlands. Adolescents who were born between April 1, 2002, and January 31, 2006, and had information on self-reported or parent-reported gender diversity and structural neuroimaging at ages 13 to 15 years were included. Data analysis was performed from April 1 to July 31, 2022.ExposuresGender-diverse experiences among adolescents were measured with selected items from the Achenbach System of Empirically Based Assessment forms and the Gender Identity/Gender Dysphoria Questionnaire for Adolescents and Adults, as reported by adolescents and/or their parents.Main Outcomes and MeasuresHigh-resolution structural neuroimaging data were collected using a 3-T magnetic resonance imaging scanner (at a single site). We used linear regression models to examine differences in global brain volumetric measures between adolescents who reported gender diversity and those who did not.ResultsThis study included 2165 participants, with a mean (SD) age of 13.8 (0.6) years at scanning. A total of 1159 participants (53.5%) were assigned female at birth and 1006 (46.5%) were assigned male at birth. With regard to maternal country of origin, 1217 mothers (57.6%) were from the Netherlands and 896 (42.4%) were from outside the Netherlands. Adolescents who reported gender diversity did not differ in global brain volumetric measures from adolescents who did not report gender diversity. In whole-brain, vertexwise analyses among adolescents assigned male at birth, thicker cortices in the left inferior temporal gyrus were observed among youths who reported gender diversity compared with those who did not. No associations were observed between gender diversity and surface area in vertexwise analyses.Conclusions and RelevanceThe findings of this cross-sectional study suggest that global brain volumetric measures did not differ between adolescents who reported gender diversity and those who did not. However, these findings further suggest that gender diversity in the general population correlates with specific brain morphologic features in the inferior temporal gyrus among youths who are assigned male at birth. Replication of these findings is necessary to elucidate the potential neurobiological basis of gender diversity in the general population. Future longitudinal studies should also investigate the directionality of these associations.

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