Biological sex classification with structural MRI data shows increased misclassification in transgender women
Claas Flint, Katharina Förster, Sophie A. Koser, Carsten Konrad, Pienie Zwitserlood, Klaus Berger, Marco Hermesdorf, Tilo Kircher, Igor Nenadic, Axel Krug, Bernhard T. Baune, Katharina Dohm, Ronny Redlich, Nils Opel, Volker Arolt, Tim Hahn, Xiaoyi Jiang, Udo Dannlowski, Dominik Grotegerd
Transgender individuals (TIs) show brain structural alterations that differ from their biological sex as well as their perceived gender. To substantiate evidence that the brain structure of TIs differs from male and female, we use a combined multivariate and univariate approach. Gray matter segments resulting from voxel-based morphometry preprocessing of N = 1753 cisgender (CG) healthy participants were used to train (N = 1402) and validate ( 20 % hold-out; N = 351) a support-vector machine classifying the biological sex. As a second validation, we classified N = 1104 patients with depression. A third validation was performed using the matched CG sample of the transgender women (TWs) application-sample. Subsequently, the classifier was applied to N = 26 TWs. Finally, we compared brain volumes of CG-men, women and TW-pre/post treatment (cross-sex hormone treatment) in a univariate analysis controlling for sexual orientation, age and total brain volume. The application of our biological sex classifier to the transgender sample resulted in a significantly lower true positive rate (TPR) (TPR-male = 56.0 %). The TPR did not differ between CG-individuals with (TPR-male = 86.9 %) and without depression ( TPR-male = 88.5 %). The univariate analysis of the transgender application-sample revealed that TW-pre/post treatment show brain structural differences from CG-women and CG-men in the putamen and insula, as well as the whole-brain analysis. Our results support the hypothesis that brain structure in TW differs from brain structure of their biological sex (male) as well as their perceived gender (female). This finding substantiates evidence that TIs show specific brain structural alterations leading to a different pattern of brain structure than CG-individuals.
Keywords: Neuroimaging - Machine Learning - Gender Dysphoria - Depression - Structural MRI - Brain Development
This repository contains the LaTeX source code for the arXiv version of this research paper.
arXiv: https://arxiv.org/abs/1911.10617v2
The research paper was accepted for publication at Neuropsychopharmacology (Internet - 9th April 2020). Available from: https://doi.org/10.1038/s41386-020-0666-3
For citations please use the data from the following BiBTeX entry (download):
@article{FlintFoerster2020,
author = {Flint, Claas and F{\"{o}}rster, Katharina and Koser, Sophie A and Konrad, Carsten and Zwitserlood, Pienie and Berger, Klaus and Hermesdorf, Marco and Kircher, Tilo and Nenadic, Igor and Krug, Axel and Baune, Bernhard T and Dohm, Katharina and Redlich, Ronny and Opel, Nils and Arolt, Volker and Hahn, Tim and Jiang, Xiaoyi and Dannlowski, Udo and Grotegerd, Dominik},
doi = {10.1038/s41386-020-0666-3},
issn = {0893-133X},
journal = {Neuropsychopharmacology},
month = {sep},
number = {10},
pages = {1758--1765},
publisher = {Springer Science and Business Media {\{}LLC{\}}},
title = {{Biological sex classification with structural MRI data shows increased misclassification in transgender women}},
url = {https://doi.org/10.1038{\%}2Fs41386-020-0666-3 https://www.nature.com/articles/s41386-020-0666-3},
volume = {45},
year = {2020}
}