the science of gender identity (part 1: genetics)

This is the first in a multi-part series surveying the current science of gender identity, particularly with regard to the transgendered population. I intend to discuss the genetic, brain anatomic, and neuropsychological findings of recent studies on the matter. As always, I will incorporate my own statistical analysis of raw study data wherever possible.

Here I start by discussing four studies involving genetic variations thought to be correlated with transsexualism. Some of these studies show promising leads toward increasing our understanding, others report limited or no findings. Limited or no findings does not imply that no genetic factors relate to transsexualism, just that none were found for the particular gene variant examined by the study.

My only beef with these studies is that they consider only one or a few genetic variations at a time. This is a limitation of the technology used. As the cost of whole-genome sequencing decreases, we’ll be able to look for simultaneous genetic variations that play a role in concert with each other.

Code and data for the analyses presented below is attached.

A Bit About the Words I’m Using

Two words I use in this post bother me, so I thought I’d explain my choice to use them.

First, I’d prefer to use the umbrella term “transgender” to label the study participants described below. However, “transgender” is too broad, as the research I describe focused on those who particularly modify their bodies to become a member of a different sex, which not all transgendered individuals want to do. Therefore I use the medical term for this population: “transsexuals”.

Second, “nucleotide variation”, which I associate below through analysis with transsexualism, implies there is a “normal” non-variation. The word is used to indicate that the particular DNA sequence involved is not present in most individuals’ genome. More common DNA variations are those that result in blue eyes vs. the more frequent brown, and certainly nothing is pathological about have blue eyes. In the same vein, I assert that nothing is pathological about transsexualism; its hypothesized genetic component is simply part of our genetic diversity.

Gene Promoter Variation rs549669867

A nucleotide variation (rs549669867) in the promoter for the gene CYP17A1 associates with female-to-male transsexualism according to a study outlined in [1]. CYP17A1 is a key gene involved in steroid metabolism, and this particular variation causes carriers to possess higher concentrations of both testosterone and estrodiol in their bodies [1]. These findings are consistent with a prevailing theory that extra testosterone causes masculinization of the female brain during fetal development, thereby contributing to development of gender dysphoria.

Here I present independent statistical reasoning based on data obtained from the study paper, which supports the researchers’ conclusions. These conclusions do not fully explain the origins of female-to-male transsexualism, as there were non-transsexuals included in the study who had the nucleotide variation, and there were transsexuals in the study who did not. However, the difference in frequencies of the variation’s occurrence between the transsexual and non-transsexual study participant groups is statistically significant.

First I’ll discuss the nucleotide variation itself. The following screenshot from the UCSC Genome Browser [2] shows 50 nucleotides upstream and downstream from the start of gene CYP17A1 on chromosome 10 of the human genome:


The variation we are examining is shown in the lower left, 34 nucleotides before the start of CYP17A1 (this is inside the “promoter” region of the gene). For the genomic strand sequenced in the study (any of two could have been chosen), the normal nucleotide at this position is a “T” and the variation is a “C”. From analysis of 1000 Genomes Project data, this variation is expected to occur on one of an individual’s two copies of chromosome 10 with a frequency of 0.02% [3].

Now the statistical analysis:

The study recruited 49 female-to-male transsexuals and 913 female controls, then sequenced their DNA in the promoter region of gene CYP17A1 to determine their genotype. The genotype could be one of three outcomes: “TT”, indicating lack of the nucleotide variation on both copies of chromosome 10; “CT”, indicating the variation occurs on only one of the chromosome 10 copies; and “CC”, indicating the variation is present on both copies of chromosome 10. The genotypes and their frequencies by group are listed in the following table:


We make two comparisons: The number of recessive genotypes vs. non-recessive genotypes (CC vs. CT + TT), and the number of dominant genotypes vs. non-dominant genotypes (TT vs. CT + CC). A variation often has to be recessive (present on both copies of its chromosome) to be biologically active, though this is not always the case.

Testing recessive vs. non-recessive genotype counts by study group using a Chi-square test yields a p-value of 0.04034, indicating a statistically significant difference exists between the transsexual and non-transsexual groups with regard to presence or absence of the recessive genotype.

Testing dominant vs. non-dominant genotype counts by study group using a Chi-square test yields a p-value of 0.06322, which is just over the commonly used threshold for declaring statistical significance.

It follows from this data and analysis that we can conclude that the recessive genotype is associated with female-to-male transsexualism. Again, this association does not explain all cases, e.g., why some non-transsexuals also have the recessive genotype, but it contributes to scientific efforts to understand transsexualism’s origins.

Gene Variation rs743572

Nucleotide variation rs743572 also impacts gene CYP17A1. Rather than residing in the promoter region of the gene as did rs549669867, this variation lies within the gene itself.

In the my analysis of this variation’s study data discussed below [4], the association between the variation and transsexualism (comparing transsexuals vs. controls) is not significant. However, the difference in the frequency of the variation between female-to-male transsexuals and male-to-female transsexuals is significant according to the statistical test I conducted. (The study authors concluded the same thing, just with different p-values). Therefore I’m reporting this variation as notable with regard to our efforts to understand the genetic underpinnings of transsexualism. The difference between this variation’s frequency in female-to-male transsexuals vs. male-to-female transsexuals may lead to insight into the origin of each outcome separately (per nominal biological sex), rather than help provide a “one size fits all” explanation for transsexualism.

rs743572 resides 139 nucleotide positions from the start of gene CYP17A1. It occurs on one of individuals’ two copies of chromosome 10 with a frequency of 41% [5]. The fact that this variation is much more common than rs549669867 probably explains why the transsexualism vs. control association for the variation I investigate below does not prove statistically significant. The following screenshot from the UCSC Genome Browser [2] shows the variation on gene CYP17A1 within chromosome 10 of the human genome:


The study [4] whose data I analyze here recruited 151 male-to-female and 142 female-to-male transsexuals. The researchers also recruited 167 male and 168 female non-transsexuals. All were Spaniards with no possibly confounding health issues. Of these subjects, 36% of the male-to-female and 45% of the female-to-male transsexuals carried the variation. 39% of the male and 38% of the female non-transsexuals also carried the variation. Presence or absence of the variation was determined through DNA sequencing. From this data I constructed the following contingency table, rounding to get whole numbers:


Performing pairwise comparisons of the count proportions using a Chi-squared goodness of fit test yields the following p-values:


As mentioned above, the only significant difference in variation proportions is in the comparison of female-to-male vs. male-to-female transsexuals. Therefore this variation does not by itself seem a strong contributor to our effort to explain the transgendered experience in terms of genetics. However, a whole-genome comparison study on similar test subjects could elucidate whether this variation interacts with other variations to form a combined association with transsexualism.

Androgen Receptor Repeat Length Variation rs193922933

A study [6] correlated the androgen receptor (AR) gene’s CAG repeat length variation (rs193922933) with male-to-female transsexualism. I feel the researchers did not perform their statistical analysis correctly, and have remedied the situation below. However my conclusion was the same.

The AR gene’s CAG repeat length is highly variable between individuals. Each occurrence of the repeat appends an extra amino acid to the androgen receptor protein, as shown below. No information about the frequency distribution of this variation was readily available [7].


Longer CAG repeat lengths are known to diminish testosterone signaling, which impacts masculinization of the brain during development [6].

The study authors sequenced the CAG repeat region of 112 male-to-female transsexuals and 258 male controls. They report the length data in the following plot (but not their raw data) [6]:


Using the GNU Image Manipulation Program, I measured each bar to determine the percentages and reconstructed the source data, re-plotted as follows:


Here we see that the CAG repeat length medians between the transsexual subjects and the controls differ by one (with the transsexual group’s median being longer), and that the interquartile limits are identical. The control group has a heavier lower tail.

The researchers compared the means using a t-test, which I am uncomfortable with due to the skew in the male controls’ distribution. Therefore I performed a quasi-Poisson regression since this is underdispersed count data. That analysis reported a statistically significant difference between the two groups (p = 0.0269).

I could not find data on the practical significance of a median difference of one CAG repeat length.

Negative Results

Another study [8], found no association between CAG repeat length variation in the AR gene and transsexualism. Furthermore, it found no association between transsexualism and variations in four other sex hormone-related genes: estrogen receptors alpha and beta, aromatase CYP19, and progesterone receptor PGR.

More Research Needed

A search of DisGeNET (a database of disease*-gene annotations) [9] for the term “transsexualism” shows only five genes and five PubMed publications covering the subject. This reveals the dearth of research on the matter. The image below showing the genes and PubMed articles extracted from the search comes from my own implementation of DisGeNET’s data within a graph database, which I discuss here.

*I of course object to DisGeNET’s labeling of “transsexualism” as a disease, and to its connection with the MeSH term “mental disorders”. I’ve contacted DisGeNET and MeSH about this issue and will report back on their response shortly.


Related Posts

the science of gender identity (part 2: brain anatomy)

the science of gender identity (part 3: psychology)

Code and Data





3 thoughts on “the science of gender identity (part 1: genetics)

Leave a Reply

Your email address will not be published.